Various embodiments herein disclose coordinating neighbor discovery between access points (APs) with auxiliary radios and APs without auxiliary radios. A corresponding wireless controller comprises a processor and a memory storing instructions that, when executed, cause the controller to perform operations. The operations comprise grouping APs into a first group of more flexible APs and a second group of less flexible APs and querying the second group of APs for a corresponding broadcast interval. The operations further comprise identifying when the second group of APs is scheduled to broadcast parameters, and a broadcast interval for each of the second group of APs and generating a schedule based on the scheduled broadcast and the broadcast interval for each of the second group of APs. The operations additionally comprise providing the generated schedule to the first group of APs and the second group of APs.
H04W 48/16 - ExplorationTraitement d'informations sur les restrictions d'accès ou les accès
H04W 8/00 - Gestion de données relatives au réseau
H04W 48/10 - Distribution d'informations relatives aux restrictions d'accès ou aux accès, p. ex. distribution de données d'exploration utilisant des informations radiodiffusées
H04W 72/52 - Critères d’affectation ou de planification des ressources sans fil sur la base des charges
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
In one aspect, a method is disclosed. The method includes transmitting, from a first anchor in an Ultra-Wide Band (UWB) network, a poll message to a second anchor associated with the UWB network, wherein the poll message includes a first indication of radar usage by the first anchor. The method includes receiving, from the second anchor at the first anchor, a response message in response to the poll message. The response message includes a second indication of radar usage by the second anchor. The method includes determining, by the first anchor, a format of at least one ranging frame to enable dual radar and downlink time difference of arrival (DL-TDoA) ranging by one or more of the first anchor and the second anchor based on the poll message and the response message.
G01S 13/75 - Systèmes utilisant la reradiation d'ondes radio, p. ex. du type radar secondaireSystèmes analogues utilisant des transpondeurs alimentés par les ondes reçues, p. ex. utilisant des transpondeurs passifs
G01S 7/00 - Détails des systèmes correspondant aux groupes , ,
In one aspect, a controller associated with an Ultra-Wide Band (UWB) network may analyze plurality of ranging methods utilized by a plurality of anchors of the UWB network to synchronize respective timings for tracking one or more tags in a geographic area. The controller may also determine a first ranging round structure that accommodates a first pair of ranging methods of the plurality of ranging methods. The first pair of ranging methods may include two distinct ranging methods of the plurality of ranging methods. The controller may transmit a first synchronization signal based on the first ranging round structure to at least a subset of the plurality of anchors to synchronize transmissions associated with tracking the one or more tags.
Devices, systems, methods, and processes for automatically generating, at least in part, a segmentation strategy. Users of workload protection solutions can initiate a process to deploy various agents onto a network with one or more operating systems. The initial scope may be defined via one or more best practices to generate a scope tree. Associated labels may be defined based on the scope design and any subnets learned from the installed agent interface subnets. Common services can also be defined based on well known ports and/or protocols. Agent-based host names can also be evaluated to define potential application groupings. A generated application dependency mapping can be applied to understand potential application boundaries and potential policy recommendations. These steps can help a user to begin their segmentation strategy when deploying a workload protection solution.
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
5.
HYBRID FIRA-OMLOX DOWNLINK TIME DIFFERENCE OF ARRIVAL STRUCTURE FOR ULTRA-WIDE BAND RANGING
The present disclosure is directed to signaling procedures for enabling co-existence of omlox and FiRa UWB standards. In one aspect, a method includes determining, for each of a plurality of ranging blocks to be used by one of a plurality of anchors in a hybrid FiRa-omlox environment, a corresponding rounding split between corresponding idle ranging rounds and active ranging rounds, the plurality of anchors including at least one FiRa-compatible anchor and at least one omlox-compatible anchor; generating each of the plurality of ranging blocks using the corresponding rounding split; and sending the plurality of ranging blocks to the plurality of anchors.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
G01S 3/18 - Systèmes pour déterminer une direction ou une déviation par rapport à une direction prédéterminée utilisant une comparaison d'amplitude de signaux provenant successivement d'antennes ou de systèmes d'antennes réceptrices ayant des caractéristiques de directivité différemment orientées ou d'un système d'antenne ayant une caractéristique de directivité à orientation variant périodiquement provenant directement d'antennes directionnelles séparées
G01S 13/02 - Systèmes utilisant la réflexion d'ondes radio, p. ex. systèmes du type radar primaireSystèmes analogues
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p. ex. gestion de la mobilité
6.
CORRELATING ENDPOINT AND NETWORK VIEWS TO IDENTIFY EVASIVE APPLICATIONS
In one embodiment, a service receives traffic telemetry data regarding encrypted traffic sent by an endpoint device in a network. The service analyzes the traffic telemetry data to infer characteristics of an application on the endpoint device that generated the encrypted traffic. The service receives, from a monitoring agent on the endpoint device, application telemetry data regarding the application. The service determines that the application is evasive malware based on the characteristics of the application inferred from the traffic telemetry data and on the application telemetry data received from the monitoring agent on the endpoint device. The service initiates performance of a mitigation action in the network, after determining that the application on the endpoint device is evasive malware.
G06F 21/44 - Authentification de programme ou de dispositif
G06F 21/52 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
7.
Systems And Methods For Scalable Machine-Learning Deployment In Anomaly Detection
Some implementations of the disclosure provided a method including operations of obtaining a data set, performing feature extraction operations resulting to extract features according to the first time window, performing aggregation operations for each feature of the extracted features with historical features resulting in a set of aggregated features, performing feature engineering on the aggregated features on a per entity basis resulting in generation of set of feature vectors, performing an anomaly detection process on the set of feature vectors including providing the set of feature vectors as input to a machine learning model resulting in generation of a label for each feature vector of the set of features, and performing a remedial action determination process including performing a threshold comparison with each label and, responsive to satisfaction of the threshold comparison by a first label, causing performance of one or more remedial actions.
Techniques described herein can perform obfuscation detection on command lines used at computing devices in a network. In response to detecting obfuscation in a command line, the disclosed techniques can output a notification for use in connection with network security analysis. The command line obfuscation detection techniques include pre-processing command line input data and converting command lines into token groups. The token groups are then provided as an input to a natural language processor or other machine learned model, which is trained to identify obfuscation probabilities associated with token groups can corresponding command lines. A notification is generated to trigger further analysis in response to an obfuscation probability exceeding a threshold obfuscation probability.
A system and method are provided for placing network functions among respective locations in a network. The locations at which the network functions are placed can be nodes and network devices within the network. These nodes can be selected, e.g., based on which network devices have available capacity and or specialized hardware (e.g., accelerator sin a data processing units (DPUs)) that is optimized for particular network functions. The network functions can include an inline network function that is provisioned directly in a data plane of one of the network devices (e.g., in-lined directly in a hardware offload device without a virtual machine and without a container). The decision of where to place the network functions can be based on a performance metric (e.g., representing available computational/memory resources at the network nodes) and/or a network-function metric (e.g., representing consumed computational/memory resources by the network functions) to improve system performance.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 41/0806 - Réglages de configuration pour la configuration initiale ou l’approvisionnement, p. ex. prêt à l’emploi [plug-and-play]
H04L 41/0816 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant une adaptation, p. ex. en réponse aux événements dans le réseau
H04L 41/082 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant des mises à jour ou des mises à niveau des fonctionnalités réseau
H04L 41/0869 - Validation de la configuration au sein d'un élément de réseau
H04L 41/0895 - Configuration de réseaux ou d’éléments virtualisés, p. ex. fonction réseau virtualisée ou des éléments du protocole OpenFlow
A computer-implemented method includes receiving, at an access point (AP) in an ultra-wide band (UWB) network from a tag, a registration request; in response to receiving the registration request, transmitting, by the AP to the tag, a registration response to complete a pairing between the tag and the AP, the registration response including an indication of support for ranging services including Two-Way Ranging (TWR) and Uplink Time Difference of Arrival (UL-TDoA); upon completion of the pairing, receiving, at the AP from the tag, a request message for obtaining a set of parameters for one of the ranging services, the request message including an identifier of a UWB component stored on the tag and a periodicity for the one of the ranging services; and sending, by the AP to the tag, a response message including the set of parameters that includes a proposed periodicity for the one of the ranging services.
In one aspect, a controller associated with an Ultra-Wide Band (UWB) network may analyze plurality of ranging methods utilized by a plurality of anchors of the UWB network to synchronize respective timings for tracking one or more tags in a geographic area. The controller may also determine a first ranging round structure that accommodates a first pair of ranging methods of the plurality of ranging methods. The first pair of ranging methods may include two distinct ranging methods of the plurality of ranging methods. The controller may transmit a first synchronization signal based on the first ranging round structure to at least a subset of the plurality of anchors to synchronize transmissions associated with tracking the one or more tags.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
12.
HYBRID FIRA-OMLOX DOWNLINK TIME DIFFERENCE OF ARRIVAL STRUCTURE FOR ULTRA-WIDE BAND RANGING
The present disclosure is directed to signaling procedures for enabling co-existence of omlox and FiRa UWB standards. In one aspect, a method includes determining, for each of a plurality of ranging blocks to be used by one of a plurality of anchors in a hybrid FiRa-omlox environment, a corresponding rounding split between corresponding idle ranging rounds and active ranging rounds, the plurality of anchors including at least one FiRa-compatible anchor and at least one omlox-compatible anchor; generating each of the plurality of ranging blocks using the corresponding rounding split; and sending the plurality of ranging blocks to the plurality of anchors.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
Embodiments are directed towards real time display of event records with an indication of previously provided extraction rules. A plurality of extraction rules may be provided to the system, such as automatically generated and/or user created extraction rules. These extraction rules may include regular expressions. A plurality of event records may be displayed to the user, such that text in a field defined by an extraction rule is emphasized in the display of the event record. The same emphasis may be provided for text in overlapping fields, or the emphasis may be somewhat different for different fields. The user interface may enable a user to select a portion of text of an event record, such as by rolling-over or clicking on an emphasized part of the event record. By selecting the portion of the event record, the interface may display each extraction rule associated with the selected portion.
G06F 7/24 - Tri, c.-à-d. extraction de données d'un ou de plusieurs supports, nouveau rangement des données dans un ordre de succession numérique ou autre, et réinscription des données triées sur le support original ou sur un support différent ou sur une série de supports
G06F 16/2458 - Types spéciaux de requêtes, p. ex. requêtes statistiques, requêtes floues ou requêtes distribuées
14.
SCALING METHOD FOR FIRA UL-TDOA AND TWR UWB RANGING
A computer-implemented method includes receiving, at an access point (AP) in an ultra-wide band (UWB) network from a tag, a registration request; in response to receiving the registration request, transmitting, by the AP to the tag, a registration response to complete a pairing between the tag and the AP, the registration response including an indication of support for ranging services including Two-Way Ranging (TWR) and Uplink Time Difference of Arrival (UL-TDoA); upon completion of the pairing, receiving, at the AP from the tag, a request message for obtaining a set of parameters for one of the ranging services, the request message including an identifier of a UWB component stored on the tag and a periodicity for the one of the ranging services; and sending, by the AP to the tag, a response message including the set of parameters that includes a proposed periodicity for the one of the ranging services.
H04W 4/02 - Services utilisant des informations de localisation
H04W 60/04 - Rattachement à un réseau, p. ex. enregistrementSuppression du rattachement à un réseau, p. ex. annulation de l'enregistrement utilisant des événements déclenchés
H04W 84/18 - Réseaux auto-organisés, p. ex. réseaux ad hoc ou réseaux de détection
15.
GENERATING NEW USER FEEDBACK IN COGNITIVE NETWORKS
In one embodiment, a device obtains a training dataset to train a machine learning model to predict a quality of experience metric for an online application accessible via a computer network. The device identifies a range of modifications to a telemetry metric in the training dataset that would be realistic with respect to the computer network and the online application. The device receives feedback from a user interface regarding the range of modifications to the telemetry metric. The device augments the training dataset with additional values of the telemetry metric in accordance with the feedback from the user interface.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 45/02 - Mise à jour ou découverte de topologie
16.
AUTOMATED POSITION ESTIMATION BASED ON COORDINATING ACCESS POINTS
Disclosed are systems, apparatuses, methods, and computer-readable media for identifying a locations of a network entities within a network. A method for identifying a location of an (AP) includes receiving a first location measurement associated with a first measurement variant and a second location measurement associated with a second measurement variant from a first AP; receiving a third location measurement associated with the first measurement variant and a fourth location measurement associated with the second measurement variant from a second AP; determining weights associated with the location measurements; determining a first location associated with the first AP and a second location associated with the second AP based on a first weight, a second weight, a third weight, and a fourth weight; determining a confidence of the first location based on a comparison of the first location measurement and the second location measurement.
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p. ex. gestion de la mobilité
G01S 5/00 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
17.
ENABLING ON-PREMISES SECURITY PER TENANT ON A MULTI-TENANT EDGE DEVICE
In one embodiment, a method includes onboarding, by an edge router, a first tenant from a network management system and determining, by the edge router, a mapping of a tenant identifier associated with the first tenant to a controller identifier associated with a controller. The method also includes reserving, by the edge router, a port number in a kernel for the first tenant and inserting, by the edge router, the tenant identifier into a first control packet. The method further includes communicating, by the edge router, the first control packet to the controller via an encrypted control connection during a first peering session. The first peering session shares the encrypted control connection with a second peering session.
This document discloses methods and systems for cohort identification. The methods and systems include improved calculations to perform cohort identification and practical applications of the improved calculations. Specifically, the systems and methods described herein may utilize key components that include enhancements of existing cohort clustering techniques with regard to selecting a number of cohort input dimensions, normalizing input data using a logarithm kernel-function, treatment of categorical data with mutually exclusive and not-mutually exclusive values, methods and visualization tool to determine appropriate number of cohorts, methods and visualization tool to compare cohorts extracted from different input dimensions, and methods to quantify the difference in cohorts. Beyond improvements to the cohort clustering techniques, also disclosed are ancillary tools to prepare input data by joining CRM and product usage data and facilitate subsequent automated action via an API to retrieve cohort results.
In one embodiment, a method includes receiving, by a first processor, a data packet for processing, the data packet including a header in an unencrypted portion of the data packet, the header having subspace ID information corresponding to a core from which the data packet was sent; saving, by the first processor, the subspace ID information; encoding, within the header, a selected subspace ID information identifying a core within the first processor to which subsequent data packets are to be received; and sending, by the first processor, in another data packet, the selected subspace ID information to a second processor that sent the data packet, the selected subspace ID information included in a header in an unencrypted portion of the data packet.
A method is disclosed wherein a device registers with a Secure Service Edge (SSE) upon VPN client startup to receive a policy configuring the client as a forwarding agent. The policy designates a Domain Name System (DNS) and data packet route. A tunnel is established between an Application Connector (ACA) agent and an Application Connector Gateway (ACG). Upon receiving a data packet via the ACG containing a request with an application destination, the device checks for an existing flow at the ACG. If none exists, the device identifies the ACA in the Application Connector Gateway Group (ACAG), replacing the packet's IP address with the ACA's. The device routes the packet through the tunnel to the identified ACA, which directs it to the application. This method optimizes routing efficiency and ensures seamless connectivity between devices and applications.
In one embodiment, a device obtains data regarding routing decisions made by a machine learning-based predictive routing engine for a network. The device determines, based on the data regarding the routing decisions, a behavior of the machine learning-based predictive routing engine. The device compares the behavior of the machine learning-based predictive routing engine to a behavioral policy for the machine learning-based predictive routing engine. The device adjusts operation of the machine learning-based predictive routing engine, when the behavior of the machine learning-based predictive routing engine violates the behavioral policy.
Disclosed are systems, apparatuses, methods, and computer-readable media for tracing multicast paths in hybrid networks. A method for tracing multicast paths in hybrid networks includes intercepting, by an edge device, a first multicast trace request transmitted by a first network device that a source device is connected to for tracing a route between the source device to a receiver device, wherein the first network device receives a message from a multicast tracing client to trace a multicast path from the receiver device to the source device; generating a second multicast trace request based on the format for the core network using information from the first multicast trace request; and transmitting the second multicast trace request from an edge network device to the receiver device using the core network, the second multicast trace request including network information related to network performance between the first network device and the edge network device
H04L 43/10 - Surveillance active, p. ex. battement de cœur, utilitaire Ping ou trace-route
H04L 45/50 - Routage ou recherche de routes de paquets dans les réseaux de commutation de données utilisant l'échange d'étiquettes, p. ex. des commutateurs d'étiquette multi protocole [MPLS]
23.
AUTOMATED GROUP OPT-IN METHOD FOR 802.11 WIRELESS NETWORKS
According to one aspect, a method includes establishing, by an access point (AP), a wireless communications link between the AP and a wireless station, wherein establishing the wireless communications link includes receiving a protected association request frame from the wireless station. The protected association request frame includes rotation pace preference information for randomized Media Access Control (MAC) address rotation management that indicates a preferred rotation pace. The method also includes selecting, by the AP, an Enhanced Data Privacy (EDP) group based on the rotation pace preference, the selected EDP group associated with epoch timing information for rotating wireless frame anonymization parameters at epoch transitions. A response frame that indicates the selected EDP group is transmitted to the wireless station. The AP maintains the wireless communications link with the wireless station based in part on the timing information for randomized MAC address rotation for the selected EDP group.
Techniques for optimizing wireless connectivity between access points and associated stations. The techniques include determining, at an access point, to enter a power save mode at a future period of time. The techniques further include generating, at the access point, a connectivity recommendation of one or more alternative connection points for maintaining wireless service among one or more stations associated with the access point. The techniques further include transmitting, prior to entering the power save mode, the connectivity recommendation to the one or more stations associated with the access point.
The current technology involves a process of determining the likelihood of a received electronic communication to a first user being malicious by a content inspection service. If the communication is deemed suspicious, it will be directed to a generative artificial intelligence (AI) tool for engagement. All subsequent communications in the same thread will also be directed to the AI tool unless the first user explicitly requests control over the thread. The AI tool will then respond to the suspicious communication while posing as the first user, but without revealing any confidential information. This process helps to prevent potential attacks by remvoing the thread of malicious communications.
In one implementation, a device may obtain operational attributes across a plurality of spans associated with a monitored transaction over a network. The device may provide the operational attributes for configuration as an operational metric attribute and as dimension attributes corresponding to the operational metric attribute. The device may generate, based on the configuration, an operational metric measurement corresponding to the operational metric attribute and one or more dimensions corresponding to the dimension attributes. The device may provide the operational metric measurement for at least one of the one or more dimensions for operational analysis.
Techniques for optical communication include transmitting a calibration pattern in an electro-optical transmitter, and tapping an output of a modulator driver of the electro-optical transmitter, the output generated based on the transmitted calibration pattern. The techniques further include determining one or more calibration parameters relating to an in-phase clock (ICLK) and quadrature clock (QCLK) for the electro-optical transmitter, based on the tapped output, and calibrating at least one of the ICLK or QCLK based on the determined one or more calibration parameters.
H04B 17/11 - SurveillanceTests d’émetteurs pour l’étalonnage
H04B 10/516 - Détails du codage ou de la modulation
H04L 25/49 - Circuits d'émissionCircuits de réception à conversion de code au transmetteurCircuits d'émissionCircuits de réception à pré-distorsionCircuits d'émissionCircuits de réception à insertion d'intervalles morts pour obtenir un spectre de fréquence désiréCircuits d'émissionCircuits de réception à au moins trois niveaux d'amplitude
28.
WIRELESS CLIENT EXPERIENCE REPORTING IN WIRELESS NETWORKS
A method for managing and controlling a wireless network includes detecting, by a wireless client, at least one operational metric associated with operations of the wireless client in a wireless local area network (WLAN) infrastructure, wherein the at least one operational metric is determined by the wireless client in response to wireless service supplied by the WLAN infrastructure, generating a client experience score based on the at least one operational metric, and transmitting the client experience score to a controller, which is configured to adjust, in response to the client experience score, at least one operational parameter of the WLAN infrastructure to cause a change to the at least one operational metric and to a subsequently generated client experience score.
In one embodiment, a method includes transmitting power in a power and data distribution system comprising at least two pairs of wires, negotiating a power level between Power Sourcing Equipment (PSE) and a Powered Device (PD) in the power and data distribution system, transmitting the power at a power level greater than 100 watts, periodically checking each of the wires for a fault, and checking for an electrical imbalance at the wires.
Devices, systems, methods, and processes for dynamic power management in network devices are described herein. Power consumption in network devices may fluctuate due to varying load conditions, leading to inefficiency if all power supply units (PSUs) in these network devices remain active all the time. To address this, a network device is provided with a power management logic that dynamically tunes a count of active PSUs in the network device based on a load demand handled by various PSUs in the network device. The power management logic may receive, from the PSUs, one or more load status signals indicating the load demand handled by the PSUs. Based on the one or more load status signals, the power management logic may determine whether to increase or decrease the count of active PSUs. Dynamically adjusting the count of active PSUs may enhance energy efficiency, reduce costs, and promote sustainability.
G06F 1/26 - Alimentation en énergie électrique, p. ex. régulation à cet effet
G06F 1/3287 - Économie d’énergie caractérisée par l'action entreprise par la mise hors tension d’une unité fonctionnelle individuelle dans un ordinateur
G06F 1/3234 - Économie d’énergie caractérisée par l'action entreprise
G06F 1/3206 - Surveillance d’événements, de dispositifs ou de paramètres initiant un changement de mode d’alimentation
G06F 1/3209 - Surveillance d’une activité à distance, p. ex. au travers de lignes téléphoniques ou de connexions réseau
31.
WIRELESS CLIENT EXPERIENCE REPORTING IN WIRELESS NETWORKS
A method for managing and controlling a wireless network includes detecting, by a wireless client, at least one operational metric associated with operations of the wireless client in a wireless local area network (WLAN) infrastructure, wherein the at least one operational metric is determined by the wireless client in response to wireless service supplied by the WLAN infrastructure, generating a client experience score based on the at least one operational metric, and transmitting the client experience score to a controller, which is configured to adjust, in response to the client experience score, at least one operational parameter of the WLAN infrastructure to cause a change to the at least one operational metric and to a subsequently generated client experience score.
In one embodiment, a method includes receiving, by a first processor, a data packet for processing, the data packet including a header in an unencrypted portion of the data packet, the header having subspace ID information corresponding to a core from which the data packet was sent; saving, by the first processor, the subspace ID information; encoding, within the header, a selected subspace ID information identifying a core within the first processor to which subsequent data packets are to be received; and sending, by the first processor, in another data packet, the selected subspace ID information to a second processor that sent the data packet, the selected subspace ID information included in a header in an unencrypted portion of the data packet.
A method is disclosed wherein a device registers with a Secure Service Edge (SSE) upon VPN client startup to receive a policy configuring the client as a forwarding agent. The policy designates a Domain Name System (DNS) and data packet route. A tunnel is established between an Application Connector (ACA) agent and an Application Connector Gateway (ACG). Upon receiving a data packet via the ACG containing a request with an application destination, the device checks for an existing flow at the ACG. If none exists, the device identifies the ACA in the Application Connector Gateway Group (ACAG), replacing the packet's IP address with the ACA's. The device routes the packet through the tunnel to the identified ACA, which directs it to the application. This method optimizes routing efficiency and ensures seamless connectivity between devices and applications.
H04L 61/4511 - Répertoires de réseauCorrespondance nom-adresse en utilisant des répertoires normalisésRépertoires de réseauCorrespondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]
34.
WIRELESS LOCAL AREA NETWORK COORDINATION BASED ON TRANSMIT POWER ENVELOPE CHANGES
In one embodiment, a method herein comprises: determining, by an access point, a future transmit power envelope (TPE) change in a wireless local area network (WLAN); sending, from the access point to a plurality of wireless stations (STAs) within the WLAN, an indication of the future TPE change based on a particular coordination parameter; and performing, by the access point, the future TPE change for the WLAN according to the particular coordination parameter. In another embodiment, a method herein comprises: receiving, by a wireless station (STA) in a wireless local area network (WLAN), an indication of a future transmit power envelope (TPE) change from an access point for the WLAN; determining, by the wireless STA and based on the indication, a particular coordination parameter for the future TPE change; and performing, by the wireless STA, the future TPE change according to the particular coordination parameter.
H04W 52/14 - Analyse séparée de la liaison montante ou de la liaison descendante
H04W 52/36 - Commande de puissance d'émission [TPC Transmission power control] utilisant les limitations de la quantité totale de puissance d'émission disponible avec une plage ou un ensemble discrets de valeurs, p. ex. incrément, variation graduelle ou décalages
H04W 84/12 - Réseaux locaux sans fil [WLAN Wireless Local Area Network]
35.
ACCESS POINT AUTHORIZATION FOR PREEMPTION IN WIRELESS TRANSMISSION
Aspects of the present disclosure are directed to providing preemption authorizations to support transmission of low latency network traffic. In one example, a method includes receiving, at an access point, a message indicating parameters associated with network traffic to be exchanged between the access point and an end device; determining, by the access point, at least one type of preemption authorization for the network traffic based on the parameters, the at least one type of preemption authorization being one or more of a flow-based preemption authorization, traffic type-based preemption authorization, and an end device-based preemption authorization; and signaling, by the access point, the at least one type of preemption authorization to the end device.
Techniques for optimizing wireless connectivity between access points and associated stations. The techniques include determining, at an access point, to enter a power save mode at a future period of time. The techniques further include generating, at the access point, an announcement indicating the power save mode. The techniques further include transmitting, prior to entering the power save mode, the announcement to one or more stations associated with the access point.
Techniques for optimizing power save operations between access points and associated stations. The techniques include initiating a power save mode on one or more links of an access point. The techniques further include receiving, in response to the initiating, a connectivity request at the access point from one or more stations associated with the access point requesting to connect to the access point via the one or more links. The techniques further include adjusting operations of the one or more links of the access point based on the connectivity request while in the power save mode.
Bucket search metric-based rebalancing across peers includes obtaining bucket search metrics of searches performed on buckets located on peer nodes. The bucket search metrics are aggregated on a per peer node basis to obtain an aggregated bucket search metric for each peer node. An average aggregated bucket search metric is calculated across the peer nodes. The first subset of the peer nodes having the aggregated bucket search metric greater than the average aggregated bucket search metric is identified. The first subset includes a source peer node of the first subset having a deviation of an aggregated bucket search metric of the source peer node from the average aggregated bucket search metric. One or more buckets on the source peer node are moved from the source peer node to at least one target peer node of a second subset of the peer nodes.
Devices, networks, systems, methods, and processes for facilitating parallel processing in ternary content addressable memory (TCAM) systems are described herein. A TCAM system including two physical TCAM blocks may detect a key-type associated with a key entry. The TCAM system can be operated in a wide search mode or a narrow search mode based on the detected key-type. In the narrow search mode, the key entry, being a narrow key, is inputted to the two physical TCAM blocks for associated data look-up. In the wide search mode, the key entry, being a wide key, is split into two segments, and one segment is inputted to one TCAM block and the other segment is inputted to the other TCAM block. The TCAM system may implement multiple logical TCAMs using the physical TCAM blocks. Thus, integrating a hybrid architecture of hardwired logic followed by programmable logic configuration, enhanced by parallel processing.
The present disclosure describe an equalizer that implements transconductor cells using switchable inverters. The equalizer includes an input line, an output line, and a first transconductor cell. The first transconductor cell includes a first inverter electrically connected between the input line and the output line, a second inverter electrically connected between the input line and the output line, and a first switch electrically coupled to the second inverter. When the first switch closes, power is provided to the second inverter.
The present disclosure provides techniques for reporting of granular information related to a station device's uplink power headroom (UPH) in trigger-based transmissions. A client device identifies one or more power limit reasons that constrain a maximum transmit power of the client device. The client device determines an UPH based on a difference between the maximum transmit power and a current transmit power of the client device. The client device transmits a message to an access point (AP), including the UPH and the one or more power limit reasons. Based on the received information, the AP determines a target RSSI for the client device. The client device receives the target RSSI and an AP transmit power level from the AP, and defines an uplink transmit power as a function of the AP transmit power level and the target RSSI.
H04W 52/36 - Commande de puissance d'émission [TPC Transmission power control] utilisant les limitations de la quantité totale de puissance d'émission disponible avec une plage ou un ensemble discrets de valeurs, p. ex. incrément, variation graduelle ou décalages
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
Aspects of this disclosure provide a method including establishing a wireless communications link between an access point and a wireless station. Establishing the wireless communications link comprises assigning the wireless station to an Enhanced Data Privacy (EDP) group that is associated with timing information for rotating wireless frame anonymization parameters at epoch transitions. The method further includes determining a privacy-enhanced association identifier (peAID) having a size greater than a size of an AID field that is used in one or more types of wireless frames on the wireless communications link. The method further includes generating an over-the-air AID (otaAID) to be used in the one or more types of wireless frames. Generating the otaAID comprises applying at least the peAID to a hash function. The method further includes transmitting, from the access point, a first wireless frame having the otaAID in the AID field.
Aspects of the present disclosure are directed to modifying use of Restricted Target Wake Up Time Service to restrict broadcasting traffic parameters sets on a per traffic category basis between an access point and an end device in a wireless network. In one aspect, a method includes transmitting, by an access point, a message to an end device connected to the access point, the message identifying for the end device a traffic type restriction policy that the access point has on reporting Restricted Target Wake Time (R-TWT) parameters for a plurality of traffic types; and receiving, from the end device, a separate Broadcast TWT Parameters Set for each one of the plurality of traffic types in accordance with the traffic type restriction policy.
Techniques are described for securely transmitting diagnostic data between a STA and an AP before the STA has successfully been on boarded at the AP. In the embodiments herein, the STA can use a key (e.g., a long-term key) to encrypt diagnostic data transmitted to the AP when the STA has not been on boarded by the AP. This key can be provided to the STA several different ways such as when the STA was provisioned to connect to a service set identifier (SSID) supported by the AP, or the STA may have previously associated with the SSID (e.g., by connecting to the same or another AP supporting the SSID during a previous session) and received or generated the key.
Techniques for optimizing wireless connectivity between access points and associated stations. The techniques include determining, at an access point, to enter a power save mode at a future period of time. The techniques further include generating, at the access point, an announcement indicating the power save mode. The techniques further include transmitting, prior to entering the power save mode, the announcement to one or more stations associated with the access point.
Techniques for optimizing wireless connectivity between access points and associated stations. The techniques include determining, at an access point, to enter a power save mode at a future period of time. The techniques further include generating, at the access point, a connectivity recommendation of one or more alternative connection points for maintaining wireless service among one or more stations associated with the access point. The techniques further include transmitting, prior to entering the power save mode, the connectivity recommendation to the one or more stations associated with the access point.
According to one aspect, a method includes establishing, by an access point (AP), a wireless communications link between the AP and a wireless station, wherein establishing the wireless communications link includes receiving a protected association request frame from the wireless station. The protected association request frame includes rotation pace preference information for randomized Media Access Control (MAC) address rotation management that indicates a preferred rotation pace. The method also includes selecting, by the AP, an Enhanced Data Privacy (EDP) group based on the rotation pace preference, the selected EDP group associated with epoch timing information for rotating wireless frame anonymization parameters at epoch transitions. A response frame that indicates the selected EDP group is transmitted to the wireless station. The AP maintains the wireless communications link with the wireless station based in part on the timing information for randomized MAC address rotation for the selected EDP group.
Ingest health monitoring includes receiving an event stream of events to store on at least one storage system and obtaining an event from the event stream. Ingest health monitoring further includes transmitting the event to a selected ingest module queue for the event, updating an output rate indicator counter for the selected ingest module queue when failure to store the event in the ingest module queue occurs, obtaining the event from the selected ingest module queue, processing the event to generate a file for the event, and transmitting the file to the at least one storage system. Ingest health monitoring further includes updating the write failure indicator counter for a storage system of the at least one storage system when failure to transmit to the storage system occurs and updating the user interface based on the output rate indicator counter and the write failure indicator counter.
In one embodiment, a device may receive a request for training data that is based on application data generated by an application executed at a data collection node, wherein the application data is associated with metadata identifiers. The device may determine one or more training data constraints that restrict use of the application data as training data. The device may generate the training data in part by excluding application data of a particular type from being included in the training data based on a match between its metadata identifier and the one or more training data constraints. The device may provide the training data to be used to train a machine learning model.
Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive disparate data and ingest certain of the data as entries of a data store that is searchable for DIQS query processing. The DIQS may receive queries to process against the received and ingested data via an exposed network interface. In one example embodiment, the DIQS receives a query identifying data to be processed, dynamically generates a query processing scheme based on the state of the data to be processed, such as streaming or at rest, and dynamically communicates the query processing scheme to a query executor based on the state of the data to be processed.
In embodiments described within the disclosure, a method of managing recommended multi-link device reconfigurations includes constructing a management frame, wherein the management frame includes at least a dedicated capability indicator for receiving an access point multi-link device link reconfiguration recommendation, transmitting the management frame, receiving a reconfiguration frame, parsing the reconfiguration frame, and initiating a multi-link reconfiguration procedure associated with the reconfiguration frame.
In one aspect, a method includes determining, at a first access point, that a transmit opportunity (TXOP) in a first Service Period (SP) of the first access point beginning at a first time extends beyond a Start Time Protection Rule (STPR) of a second access point at a second time, and overlaps with a second SP of the second access point that starts at the second time after the first time; continuing transmissions, by the first access point, in the TXOP of the first access point during the second SP; determining that the second access point has traffic to transmit; and granting, by the first access point, a portion of the TXOP of the first access point to the second access point.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
Aspects of this disclosure provide a method including establishing a wireless communications link between an access point and a wireless station. Establishing the wireless communications link comprises assigning the wireless station to an Enhanced Data Privacy (EDP) group that is associated with timing information for rotating wireless frame anonymization parameters at epoch transitions. The method further includes determining a privacy-enhanced association identifier (peAID) having a size greater than a size of an AID field that is used in one or more types of wireless frames on the wireless communications link. The method further includes generating an over- the-air AID (otaAID) to be used in the one or more types of wireless frames. Generating the otaAID comprises applying at least the peAID to a hash function. The method further includes transmitting, from the access point, a first wireless frame having the otaAID in the AID field.
The present disclosure provides techniques for reporting of granular information related to a station device's uplink power headroom (UPH) in trigger based transmissions. A client device identifies one or more power limit reasons that constrain a maximum transmit power of the client device. The client device determines an UPH based on a difference between the maximum transmit power and a current transmit power of the client device. The client device transmits a message to an access point (AP), including the UPH and the one or more power limit reasons. Based on the received information, the AP determines a target RSSI for the client device. The client device receives the target RSSI and an AP transmit power level from the AP, and defines an uplink transmit power as a function of the AP transmit power level and the target RSSI.
H04W 52/14 - Analyse séparée de la liaison montante ou de la liaison descendante
H04W 52/24 - Commande de puissance d'émission [TPC Transmission power control] le TPC étant effectué selon des paramètres spécifiques utilisant le rapport signal sur parasite [SIR Signal to Interference Ratio] ou d'autres paramètres de trajet sans fil
H04W 52/36 - Commande de puissance d'émission [TPC Transmission power control] utilisant les limitations de la quantité totale de puissance d'émission disponible avec une plage ou un ensemble discrets de valeurs, p. ex. incrément, variation graduelle ou décalages
Techniques are described for securely transmitting diagnostic data between a STA and an AR before the STA has successfully been on boarded at the AR. In the embodiments herein, the STA can use a key (e.g., a long-term key) to encrypt diagnostic data transmitted to the AR when the STA has not been on boarded by the AR. This key can be provided to the STA several different ways such as when the STA was provisioned to connect to a service set identifier (SSID) supported by the AR, or the STA may have previously associated with the SSID (e.g., by connecting to the same or another AR supporting the SSID during a previous session) and received or generated the key.
Devices, systems, methods, and processes for dynamic power management in network devices are described herein. Power consumption in network devices may fluctuate due to varying load conditions, leading to inefficiency if all power supply units (PSUs) in these network devices remain active all the time. To address this, a network device is provided with a power management logic that dynamically tunes a count of active PSUs in the network device based on a load demand handled by various PSUs in the network device. The power management logic may receive, from the PSUs, one or more load status signals indicating the load demand handled by the PSUs. Based on the one or more load status signals, the power management logic may determine whether to increase or decrease the count of active PSUs. Dynamically adjusting the count of active PSUs may enhance energy efficiency, reduce costs, and promote sustainability.
In one embodiment, a method herein comprises: determining, by an access point, a future transmit power envelope (TPE) change in a wireless local area network (WLAN); sending, from the access point to a plurality of wireless stations (STAs) within the WLAN, an indication of the future TPE change based on a particular coordination parameter; and performing, by the access point, the future TPE change for the WLAN according to the particular coordination parameter. In another embodiment, a method herein comprises: receiving, by a wireless station (STA) in a wireless local area network (WLAN), an indication of a future transmit power envelope (TPE) change from an access point for the WLAN; determining, by the wireless STA and based on the indication, a particular coordination parameter for the future TPE change; and performing, by the wireless STA, the future TPE change according to the particular coordination parameter.
Communication systems, devices, and methods for provisioning one or more auxiliary antennas are provided. A communication system includes a network device and a set of external antennas. The network device includes a set of integral antennas and one or more auxiliary connectors. The integral antennas generate at least one beam pattern defining a first coverage area corresponding, for example, to an area in front of the network device. The external antennas are couplable to the auxiliary connectors to generate one or more beam patterns defining a second coverage area disparate from the first coverage area. The second coverage area corresponds to an area below or behind the network device. A control logic detects and provisions the coupled external antennas based on one or more user inputs or a self-identifying antenna functionality, and by selectively re-routing a radio frequency signal path from the integral antennas to the auxiliary connectors.
In one aspect, a method includes determining, at a first access point, that a transmit opportunity (TXOP) in a first Service Period (SP) of the first access point beginning at a first time extends beyond a Start Time Protection Rule (STPR) of a second access point at a second time, and overlaps with a second SP of the second access point that starts at the second time after the first time; continuing transmissions, by the first access point, in the TXOP of the first access point during the second SP; determining that the second access point has traffic to transmit; and granting, by the first access point, a portion of the TXOP of the first access point to the second access point.
Aspects of the present disclosure are directed to a mechanism for an access point to successfully handover a portion of the access point's transmission opportunity window to a neighboring access point by forcing other access points to backoff from medium contention during the handover (for the duration of the handover). In one aspect, a method includes determining, at a first access point, to grant at least a portion of a transmission opportunity (TXOP) of the first access point to a second access point; generating a signal to include an indication of a Dynamic Start Time Protection (DSTP) for the second access point, wherein the DSTP indicates to other nearby access points not to contend with the second access point after the first access point completes use of the TXOP; and transmitting the signal to at least the other nearby access points.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
A method for coordinating transmissions by an access point (AP) of a plurality of APs in a wireless network includes monitoring, by the AP, a plurality of C-RTWT (Coordinated-Restricted Target Wake Time) agreements in a neighborhood of the AP; determining, by the AP and using the plurality of C-RTWT agreements, a parameter indicative of congestion or sparsity of Start Time Protection Rules (STPRs) in the neighborhood; and modifying, by the AP, at least one C-RTWT agreement of the plurality of C-RTWT agreements to reach a target spacing among the STPRs.
Aspects of the present disclosure are directed to a hybrid structure for switching between traffic-first mode and access point-first mode when coordinating traffic transmission among access points in a wireless network. In one aspect, a multi-access point coordination method includes determining, at an access point, whether a triggering condition exists for switching between a traffic-first mode and an access point-first mode or vice-versa when coordinating traffic transmission with other neighboring access points, wherein the triggering condition is associated with Start Time Protection Rules (STPRs) of the access point and the other neighboring access points; and switching from one of the traffic-first mode and the access point-first mode to another one of the traffic-first mode and the access point-first mode upon detecting the triggering condition.
H04W 72/54 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
63.
STREAM CLASSIFICATION SERVICE FOR EVENT-BASED TRAFFIC WITH PREEMPTION REQUIREMENTS
Aspects of the present disclosure are directed to receiving, at an access point (AP) from an endpoint, a stream classification service (SCS) request. The SCS request identifies one or more of QoS characteristics and preemption requirements for a traffic flow originating from the endpoint. The method includes determining, by the AP and based on a policy, whether the AP can accept the SCS request for the traffic flow, and transmitting, by the AP and to the endpoint, an SCS response indicating whether the AP can accept the SCS request for the traffic flow or not.
H04W 28/02 - Gestion du trafic, p. ex. régulation de flux ou d'encombrement
H04L 47/2441 - Trafic caractérisé par des attributs spécifiques, p. ex. la priorité ou QoS en s'appuyant sur la classification des flux, p. ex. en utilisant des services intégrés [IntServ]
64.
ENABLING STATIONS TO INFLUENCE ACCESS POINT POWER SAVE
Techniques for optimizing power save operations between access points and associated stations. The techniques include initiating a power save mode on one or more links of an access point. The techniques further include receiving, in response to the initiating, a connectivity request at the access point from one or more stations associated with the access point requesting to connect to the access point via the one or more links. The techniques further include adjusting operations of the one or more links of the access point based on the connectivity request while in the power save mode.
Aspects of the present disclosure are directed to providing preemption authorizations to support transmission of low latency network traffic. In one example, a method includes receiving, at an access point, a message indicating parameters associated with network traffic to be exchanged between the access point and an end device; determining, by the access point, at least one type of preemption authorization for the network traffic based on the parameters, the at least one type of preemption authorization being one or more of a flow-based preemption authorization, traffic type-based preemption authorization, and an end device-based preemption authorization; and signaling, by the access point, the at least one type of preemption authorization to the end device.
According to one aspect, a method includes establishing, by an access point (AP), a wireless communications link between the AP and a wireless station, wherein establishing the wireless communications link includes receiving a protected association request frame from the wireless station. The protected association request frame includes rotation pace preference information for randomized Media Access Control (MAC) address rotation management that indicates a preferred rotation pace. The method also includes selecting, by the AP, an Enhanced Data Privacy (EDP) group based on the rotation pace preference, the selected EDP group associated with epoch timing information for rotating wireless frame anonymization parameters at epoch transitions. A response frame that indicates the selected EDP group is transmitted to the wireless station. The AP maintains the wireless communications link with the wireless station based in part on the timing information for randomized MAC address rotation for the selected EDP group.
In a computer-implemented method for configuring a distributed computer system comprising a plurality of nodes of a plurality of node classes, configuration files for a plurality of nodes of each of the plurality of node classes are stored in a central repository. The configuration files include information representing a desired system state of the distributed computer system, and the distributed computer system operates to keep an actual system state of the distributed computer system consistent with the desired system state. The plurality of node classes includes forwarder nodes for receiving data from an input source, indexer nodes for indexing the data, and search head nodes for searching the data. Responsive to receiving changes to the configuration files, the changes are propagated to nodes of the plurality of nodes impacted by the changes based on a node class of the nodes impacted by the changes.
H04L 67/06 - Protocoles spécialement adaptés au transfert de fichiers, p. ex. protocole de transfert de fichier [FTP]
H04L 41/0813 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres
H04L 41/084 - Configuration en utilisant des informations préexistantes, p. ex. en utilisant des gabarits ou en copiant à partir d’autres éléments
H04L 41/0853 - Récupération de la configuration du réseauSuivi de l’historique de configuration du réseau en recueillant activement des informations de configuration ou en sauvegardant les informations de configuration
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
H04L 69/329 - Protocoles de communication intra-couche entre entités paires ou définitions d'unité de données de protocole [PDU] dans la couche application [couche OSI 7]
68.
AN ENHANCED SERVICE NODE NETWORK INFRASTRUCTURE FOR L2/L3 GW IN CLOUD
Disclosed herein are systems, methods, and computer-readable media for managing Layer 2 (L2) and Layer 3 (L3) policies. Traffic is routed from a first VM to a first CGW within a Service Node, where the Service Node can include a centralized policy for both L2 functions and L3 functions, and the first CGW can integrate both L2 gateways and L3 gateways. Based on a floating IP address of the packet, the traffic is routed within the Service Node, the traffic being routed by an access BD from an ingress BD-VIF to an egress BD-VIF. The traffic is then routed from a second CGW that integrates both L2 gateways and L3 gateways to the destination VM.
A data intake and query system can process a query to identify subquery tokens corresponding to subqueries to be executed by external data systems. The data intake and query system can process the subquery tokens to generate modified subqueries to be executed by the external data systems. The modified subqueries can cause the external data system to return metadata associated with the events processed by the external data systems during executing of the modified subqueries.
According to an embodiment, a system comprises one or more processors and one or more computer-readable non-transitory storage media comprising instructions that, when executed by the one or more processors, cause one or more components of the system to perform operations. The operations comprise determining that an endpoint device has requested to discover a location of a protected resource that is protected by a gateway, determining whether the endpoint device has provided a token that is valid, and permitting the endpoint device to discover the location of the protected resource based on determining that the endpoint device has provided the token that is valid. The token indicates that the endpoint device successfully completed a first multi-factor authentication procedure in connection with accessing an authentication enforcement resource.
The present technology provides solutions for optimizing communications between nodes and can include receiving, by a first node from a second node, an advertisement indicating an advertisement transport protocol supported by the second node, where the first node supports a plurality of transport protocols, and the advertisement transport protocol is one of the plurality of transport protocols, where the first node and the second node are nodes of a border gateway protocol (BGP) community, receiving, by the first node, from a requesting node a request to join the BGP community, where the request includes an attribute indicating a request transport protocol supported by the requesting node, allocating, by the first node and based on the attribute, a resource for the request transport protocol supported by the requesting node, and providing, by the first node, a notification to the second node indicating allocation of the resource for the request transport protocol.
A method of application program interface (API) endpoint host redirection may include with an intelligent domain name system (DNS) engine (IDE) associated with a containerized service within a pod of a mesh network, snooping a DNS query from the containerized service, identifying within the DNS query, an API endpoint name, snooping a DNS response associated with the DNS query, identifying an Internet protocol (IP) address associated with the API endpoint name, transmitting the API endpoint name and the IP address to a controller, receiving, from the controller, a list of safe API endpoint hosts with no known security vulnerabilities based on security data obtained from at least one security service, caching, at the IDE, the list of safe API endpoint hosts including safe IP addresses, and transmitting to the containerized service, via the IDE, IP addresses of safe API endpoint hosts within the list of safe API endpoint hosts.
Communication systems, devices, and methods for provisioning one or more auxiliary antennas are provided. A communication system includes a network device and a set of external antennas. The network device includes a set of integral antennas and one or more auxiliary connectors. The integral antennas generate at least one beam pattern defining a first coverage area corresponding, for example, to an area in front of the network device. The external antennas are couplable to the auxiliary connectors to generate one or more beam patterns defining a second coverage area disparate from the first coverage area. The second coverage area corresponds to an area below or behind the network device. A control logic detects and provisions the coupled external antennas based on one or more user inputs or a self-identifying antenna functionality, and by selectively re-routing a radio frequency signal path from the integral antennas to the auxiliary connectors.
H01Q 1/24 - SupportsMoyens de montage par association structurale avec d'autres équipements ou objets avec appareil récepteur
H01Q 3/24 - Dispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne faisant varier l'orientation, par commutation de l'énergie fournie, d'un élément actif rayonnant à un autre, p. ex. pour commutation du lobe
H01Q 3/26 - Dispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne faisant varier la phase relative ou l’amplitude relative et l’énergie d’excitation entre plusieurs éléments rayonnants actifsDispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne faisant varier la distribution de l’énergie à travers une ouverture rayonnante
H01Q 21/28 - Combinaisons d'unités ou systèmes d'antennes sensiblement indépendants et n’interagissant pas entre eux
H01Q 25/00 - Antennes ou systèmes d'antennes fournissant au moins deux diagrammes de rayonnement
H01Q 3/04 - Dispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne utilisant un mouvement mécanique de l'ensemble d'antenne ou du système d'antenne pour faire varier une coordonnée de l'orientation
H01Q 1/22 - SupportsMoyens de montage par association structurale avec d'autres équipements ou objets
H01Q 5/50 - Dispositions d’alimentation ou d’adaptation pour un fonctionnement à large bande ou multibande
74.
ENABLING IMPROVED MULTI-LINK RECONFIGURATION WHEN DELETING CURRENT LINK
In various embodiments described herein methods, systems, and devices for facilitating improved multi-link reconfiguration, the method includes constructing a link reconfiguration request frame, transmitting the link configuration request frame, receiving a link reconfiguration response frame, processing the received link configuration response frame, transmitting an acknowledgment frame, and transitioning link operations.
H04W 76/34 - Libération sélective de connexions en cours
H04L 41/0213 - Protocoles de gestion de réseau normalisés, p. ex. protocole de gestion de réseau simple [SNMP]
H04L 41/0813 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres
H04W 36/28 - La resélection étant déclenchée par des paramètres spécifiques par des paramètres de communication agréés ou négociés impliquant une pluralité de liaisons, p. ex. des liaisons multi-appels ou multi-porteuses
H04W 76/15 - Établissement de connexions à liens multiples sans fil
H04W 84/12 - Réseaux locaux sans fil [WLAN Wireless Local Area Network]
75.
TRANSMISSION BACKOFF FOR TXOP HANDOVER BETWEEN ACCESS POINTS IN WIRELESS NETWORKS
Aspects of the present disclosure are directed to a mechanism for an access point to successfully handover a portion of the access point's transmission opportunity window to a neighboring access point by forcing other access points to backoff from medium contention during the handover (for the duration of the handover). In one aspect, a method includes determining, at a first access point, to grant at least a portion of a transmission opportunity (TXOP) of the first access point to a second access point; generating a signal to include an indication of a Dynamic Start Time Protection (DSTP) for the second access point, wherein the DSTP indicates to other nearby access points not to contend with the second access point after the first access point completes use of the TXOP; and transmitting the signal to at least the other nearby access points.
A method for coordinating transmissions by an access point (AP) of a plurality of APs in a wireless network includes monitoring, by the AP, a plurality of C-RTWT (Coordinated-Restricted Target Wake Time) agreements in a neighborhood of the AP; determining, by the AP and using the plurality of C-RTWT agreements, a parameter indicative of congestion or sparsity of Start Time Protection Rules (STPRs) in the neighborhood; and modifying, by the AP, at least one C-RTWT agreement of the plurality of C-RTWT agreements to reach a target spacing among the STPRs.
77.
ADAPTING RESTRICTED TARGET WAKE TIME TO PROVIDE TRAFFIC CLASSIFICATION GRANULARITY
Aspects of the present disclosure are directed to modifying use of Restricted Target Wake Up Time Service to restrict broadcasting traffic parameters sets on a per traffic category basis between an access point and an end device in a wireless network. In one aspect, a method includes transmitting, by an access point, a message to an end device connected to the access point, the message identifying for the end device a traffic type restriction policy that the access point has on reporting Restricted Target Wake Time (R-TWT) parameters for a plurality of traffic types; and receiving, from the end device, a separate Broadcast TWT Parameters Set for each one of the plurality of traffic types in accordance with the traffic type restriction policy.
Aspects of the present disclosure are directed to a hybrid structure for switching between traffic-first mode and access point-first mode when coordinating traffic transmission among access points in a wireless network. In one aspect, a multi-access point coordination method includes determining, at an access point, whether a triggering condition exists for switching between a traffic-first mode and an access point-first mode or vice-versa when coordinating traffic transmission with other neighboring access points, wherein the triggering condition is associated with Start Time Protection Rules (STPRs) of the access point and the other neighboring access points; and switching from one of the traffic-first mode and the access point-first mode to another one of the traffic-first mode and the access point-first mode upon detecting the triggering condition.
H04W 74/0816 - Accès non planifié, p. ex. ALOHA utilisant une détection de porteuse, p. ex. accès multiple par détection de porteuse [CSMA] avec évitement de collision
H04W 84/12 - Réseaux locaux sans fil [WLAN Wireless Local Area Network]
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer hardware; Computer networking hardware; Computer software; Downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; downloadable software for administration of computer networks and for computer network observability; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; downloadable computer software for computer network management; downloadable software for adaptive risk-based decision making; downloadable software for operating, accessing, and deploying AI infrastructure; downloadable software for processing data and information using an AI infrastructure; downloadable software for computer networking and wide area networking; downloadable software for optimizing enterprise connectivity; downloadable software for edge computing and edge networking; downloadable software for designing, deploying, and managing AI infrastructure; downloadable software for implementing and optimizing cloud-managed network operations; downloadable software for customer relationship management (CRM); downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; downloadable software for analyzing and reporting on computer network and computer system health and efficiency; downloadable software for troubleshooting computer software and hardware problems; downloadable software for designing, deploying, and managing computer systems and computer networks; downloadable software for business risk management; downloadable software for computer system and computer network security; downloadable software for generating product and service recommendations; downloadable personal assistant software; downloadable software for customer subscription and purchase management; downloadable software for customer identity management; downloadable software for generating recommendations for ensuring regulatory compliance Customer relationship management; Business risk management; Business risk assessment services; Business project management services; Advice and information about customer services and product management Providing online non-downloadable software; Software as a service (SaaS) services; Platform as a service (PaaS) services); Providing online non-downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; Providing online non-downloadable software for administration of computer networks and for computer network observability; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Providing online non-downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; Providing online non-downloadable computer software for computer network management; Providing online non-downloadable software for adaptive risk-based decision making; Providing online non-downloadable software for operating, accessing, and deploying AI infrastructure; Providing online non-downloadable software for processing data and information using an AI infrastructure; Providing online non-downloadable software for computer networking and wide area networking; Providing online non-downloadable software for optimizing enterprise connectivity; Providing online non-downloadable software for edge computing and edge networking; Providing online non-downloadable software for designing, deploying, and managing AI infrastructure; Providing online non-downloadable software for implementing and optimizing cloud-managed network operations; Providing online non-downloadable software for customer relationship management (CRM); Providing online non-downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; Providing online non-downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; Providing online non-downloadable software for analyzing and reporting on computer network and computer system health and efficiency; Providing online non-downloadable software for troubleshooting computer software and hardware problems; Providing online non-downloadable software for designing, deploying, and managing computer systems and computer networks; Providing online non-downloadable software for business risk management; Providing online non-downloadable software for computer system and computer network security; Providing online non-downloadable software for generating product and service recommendations; Providing online non-downloadable personal assistant software; Providing online non-downloadable software for customer subscription and purchase management; Providing online non-downloadable software for customer identity management; Providing online non-downloadable software for generating recommendations for ensuring regulatory compliance; monitoring of computer systems operation by remote access; technical support services, namely, troubleshooting computer software problems, and services for the updating, maintenance, installation, repair, and customization of computer software; planning, design and implementation of computer technologies for others; research in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing information in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing technical information in the field of computer software applications; Information Technology consulting services
The disclosed embodiments include a method performed by a computer system. The method includes receiving first user input defining a filter of an anomaly action rule, the filter defining at least one of an attribute of an anomaly or an attribute of a computer network entity. The method also includes receiving second user input defining an action of the anomaly action rule. The method further includes generating the anomaly action rule based on the first user input and the second user input, wherein the anomaly action rule causes performance of the action upon detecting an anomaly on the computer network that satisfies the anomaly action rule.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Computer hardware; Computer networking hardware; Computer software; Downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; downloadable software for administration of computer networks and for computer network observability; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; downloadable computer software for computer network management; downloadable software for adaptive risk-based decision making; downloadable software for operating, accessing, and deploying AI infrastructure; downloadable software for processing data and information using an AI infrastructure; downloadable software for computer networking and wide area networking; downloadable software for optimizing enterprise connectivity; downloadable software for edge computing and edge networking; downloadable software for designing, deploying, and managing AI infrastructure; downloadable software for implementing and optimizing cloud-managed network operations; downloadable software for customer relationship management (CRM); downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; downloadable software for analyzing and reporting on computer network and computer system health and efficiency; downloadable software for troubleshooting computer software and hardware problems; downloadable software for designing, deploying, and managing computer systems and computer networks; downloadable software for business risk management; downloadable software for computer system and computer network security; downloadable software for generating product and service recommendations; downloadable personal assistant software; downloadable software for customer subscription and purchase management; downloadable software for customer identity management; downloadable software for generating recommendations for ensuring regulatory compliance. (1) Customer relationship management; Business risk management; Business risk assessment services; Business project management services; Advice and information about customer services and product management.
(2) Providing online non-downloadable software; Software as a service (SaaS) services; Platform as a service (PaaS) services); Providing online non-downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; Providing online non-downloadable software for administration of computer networks and for computer network observability; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Providing online non-downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; Providing online non-downloadable computer software for computer network management; Providing online non-downloadable software for adaptive risk-based decision making; Providing online non-downloadable software for operating, accessing, and deploying AI infrastructure; Providing online non-downloadable software for processing data and information using an AI infrastructure; Providing online non-downloadable software for computer networking and wide area networking; Providing online non-downloadable software for optimizing enterprise connectivity; Providing online non-downloadable software for edge computing and edge networking; Providing online non-downloadable software for designing, deploying, and managing AI infrastructure; Providing online non-downloadable software for implementing and optimizing cloud-managed network operations; Providing online non-downloadable software for customer relationship management (CRM); Providing online non-downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; Providing online non-downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; Providing online non-downloadable software for analyzing and reporting on computer network and computer system health and efficiency; Providing online non-downloadable software for troubleshooting computer software and hardware problems; Providing online non-downloadable software for designing, deploying, and managing computer systems and computer networks; Providing online non-downloadable software for business risk management; Providing online non-downloadable software for computer system and computer network security; Providing online non-downloadable software for generating product and service recommendations; Providing online non-downloadable personal assistant software; Providing online non-downloadable software for customer subscription and purchase management; Providing online non-downloadable software for customer identity management; Providing online non-downloadable software for generating recommendations for ensuring regulatory compliance; monitoring of computer systems operation by remote access; technical support services, namely, troubleshooting computer software problems, and services for the updating, maintenance, installation, repair, and customization of computer software; planning, design and implementation of computer technologies for others; research in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing information in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing technical information in the field of computer software applications; Information Technology consulting services.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer hardware; Computer networking hardware; Computer software; Downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; downloadable software for administration of computer networks and for computer network observability; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; downloadable computer software for computer network management; downloadable software for adaptive risk-based decision making; downloadable software for operating, accessing, and deploying AI infrastructure; downloadable software for processing data and information using an AI infrastructure; downloadable software for computer networking and wide area networking; downloadable software for optimizing enterprise connectivity; downloadable software for edge computing and edge networking; downloadable software for designing, deploying, and managing AI infrastructure; downloadable software for implementing and optimizing cloud-managed network operations; downloadable software for customer relationship management (CRM); downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; downloadable software for analyzing and reporting on computer network and computer system health and efficiency; downloadable software for troubleshooting computer software and hardware problems; downloadable software for designing, deploying, and managing computer systems and computer networks; downloadable software for business risk management; downloadable software for computer system and computer network security; downloadable software for generating product and service recommendations; downloadable personal assistant software; downloadable software for customer subscription and purchase management; downloadable software for customer identity management; downloadable software for generating recommendations for ensuring regulatory compliance. Customer relationship management; Business risk management; Business risk assessment services; Business project management services; Advice and information about customer services and product management. Providing online non-downloadable software; Software as a service (SaaS) services; Platform as a service ((PaaS) services); Providing online non-downloadable artificial intelligence software, namely, software for implementing algorithms and programs in the fields of artificial intelligence and machine learning; Providing online non-downloadable software for administration of computer networks and for computer network observability; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for monitoring of computer systems and networks; Providing online non-downloadable software using artificial intelligence, machine learning, and generative artificial intelligence for cloud and data access, management and collection; Providing online non-downloadable data center software for the collection, analysis, editing, organizing, modifying, book marking, transmission, storage, and sharing of data and information; Providing online non-downloadable computer software for computer network management; Providing online non-downloadable software for adaptive risk-based decision making; Providing online non-downloadable software for operating, accessing, and deploying AI infrastructure; Providing online non-downloadable software for processing data and information using an AI infrastructure; Providing online non-downloadable software for computer networking and wide area networking; Providing online non-downloadable software for optimizing enterprise connectivity; Providing online non-downloadable software for edge computing and edge networking; Providing online non-downloadable software for designing, deploying, and managing AI infrastructure; Providing online non-downloadable software for implementing and optimizing cloud-managed network operations; Providing online non-downloadable software for customer relationship management (CRM); Providing online non-downloadable software for customer experience management (CXM); Downloadable software for digital experience monitoring; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting computer networks through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer relationship management (CRM) software through artificial intelligence and machine learning; Providing online non-downloadable software featuring a virtual assistant for use in managing, monitoring, and troubleshooting customer experience management (CXM) software through artificial intelligence and machine learning; Providing online non-downloadable software using artificial intelligence for computer hardware and software customer onboarding and providing suggestions and advice relating to maintaining, optimizing, customizing, and making supplemental purchases relating to computer hardware and software; Providing online non-downloadable software for analyzing and reporting on computer network and computer system health and efficiency; Providing online non-downloadable software for troubleshooting computer software and hardware problems; Providing online non-downloadable software for designing, deploying, and managing computer systems and computer networks; Providing online non-downloadable software for business risk management; Providing online non-downloadable software for computer system and computer network security; Providing online non-downloadable software for generating product and service recommendations; Providing online non-downloadable personal assistant software; Providing online non-downloadable software for customer subscription and purchase management; Providing online non-downloadable software for customer identity management; Providing online non-downloadable software for generating recommendations for ensuring regulatory compliance; monitoring of computer systems operation by remote access; technical support services, namely, troubleshooting computer software problems, and services for the updating, maintenance, installation, repair, and customization of computer software; planning, design and implementation of computer technologies for others; research in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing information in the fields of artificial intelligence, machine learning, and generational artificial intelligence; providing technical information in the field of computer software applications; Information Technology consulting services.
83.
ENABLING IMPROVED MULTI-LINK RECONFIGURATION WHEN DELETING CURRENT LINK
In various embodiments described herein methods, systems, and devices for facilitating improved multi-link reconfiguration, the method includes constructing a link reconfiguration request frame, transmitting the link configuration request frame, receiving a link reconfiguration response frame, processing the received link configuration response frame, transmitting an acknowledgment frame, and transitioning link operations.
Embodiments relate to a method and an electronic device for modifying a user interface of the electronic device. The method includes detecting, on the electronic device, a selection of a multi-keypad configuration among a plurality of multi-keypad configurations. Based on the selection of the multi-keypad configuration, a plurality of virtual keys are displayed on the user interface. The method includes receiving, on the user interface, a user touch gestures to configure one or more of the plurality of virtual keys to generate a virtual keyboard. The method includes updating machine learning models, image classifier models, and memory of the electronic device to update and store the generated virtual keyboard including the configuration of the one or more of the plurality of virtual keys to initiate user authentication in real time.
G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique
G06F 3/04886 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels par partition en zones à commande indépendante de la surface d’affichage de l’écran tactile ou de la tablette numérique, p. ex. claviers virtuels ou menus
In part, the disclosure relates to opto-electrical system. The system may include a waveguide defining an optical input and an optical output; a thermo-optic phase shifter (TOPS) that includes a first electrical contact and a second electrical contact, and a resistive heater in electrical communication with the first electrical contact and the second electrical contact, the TOPS configured to change a first phase of light entering the optical input to a second phase for light exiting the optical output, the TOPS having a resistance RTOPS, the TOPS in thermal communication with the waveguide; a voltage source in electrical communication with the first electrical contact; and a resistor that includes a first end and a second end, the resistor having a resistance RS, wherein the first end is grounded, wherein the second end is in electrical communication with the second electrical contact.
G02F 1/01 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur
G02F 1/21 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur par interférence
G02F 1/225 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur par interférence dans une structure de guide d'ondes optique
86.
CAPABILITY SIGNALING FOR LINK RECONFIGURATION RECOMMENDATION
In embodiments described within the disclosure, a method of managing recommended multi-link device reconfigurations includes constructing a management frame, wherein the management frame includes at least a dedicated capability indicator for receiving an access point multi-link device link reconfiguration recommendation, transmitting the management frame, receiving a reconfiguration frame, parsing the reconfiguration frame, and initiating a multi-link reconfiguration procedure associated with the reconfiguration frame.
An apparatus configured to determine sets of untraceable clock domains in the communication network may comprise a memory and a processor communicatively coupled to one another. The processor may be configured to select a clock as a Precision Time Protocol (PTP) clock, calculate a time drift associated with another clock, and average the time drift over multiple successive PTP timestamps. Further, the processor may be configured to generate a report indicating whether the clock is offset with respect to a PTP clock based on whether an average of the time drift over the successive PTP timestamps is higher than the predefined threshold.
Signaling Multi-Link Device (MLD) capabilities is provided. Signaling MLD capabilities can comprise maintaining, by a non-Access Point (AP) Multi-Link Device (MLD), an association with an AP MLD, the association comprising one or more setup links between the non-AP MLD and the AP MLD, each setup link established between an affiliated non-AP station (STA) of the non-AP MLD and an affiliated AP of the AP MLD. To add a link, the non-AP MLD generates and transmits to the AP MLD a Link Reconfiguration Request frame comprising a Reconfiguration Multi-Link element with one or more subfields, including an Extended MLD Capabilities and Operations subfield, comprising data indicating MLD capabilities of the non-AP MLD. Responsive to receiving a Link Reconfiguration Response frame indicating a success from the AP MLD, the non-AP MLD adds the link to the one or more setup links of the association between the AP MLD and the non-AP MLD.
In one embodiment, a method receives a secret and a passwordless login request using a credential provider of the client device. The method pairs the credential provider of the client device with a trusted platform module (TPM) associated with a computing device. The method encrypts, using the TPM of the computing device, the secret with a hardware-bound key associated with the computing device. The method receives, from the client device, a push notification associated with the passwordless login request. The method obtains, from the client device, biometric authentication data and a nonce encrypted with a public key. The method validates a proximity of the biometric authentication data and determine a decrypted nonce by decrypting the nonce using a private key associated with the client device. The method validates the decrypted nonce with the secret. In response to determining the decrypted nonce is valid, the method approves the passwordless login request.
Embodiments are disclosed for a data analysis tool for facilitating iterative and exploratory analysis of large sets of data. In some embodiments a data analysis tool includes a graphical user interface through which an interactive set of field identifiers is displayed. Each of the listed field identifiers may reference fields associated with a set of events returned in response to a search query, the set of events including machine data produced by components within an information technology (IT) environment that reflects activity in the IT environment. In response to user selections of field identifiers included in the displayed set, a data analysis tool may cause display of manipulable visualizations based on values included in fields referenced by the selected field identifiers.
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
First event data, indicative of a first activity on a computer network and second event data indicative of a second activity on the computer network, is received. A first machine learning anomaly detection model is applied to the first event data, by a real-time analysis engine operated by the threat indicator detection system in real time, to detect first anomaly data. A second machine learning anomaly detection model is applied to the first anomaly data and the second event data, by a batch analysis engine operated by the threat indicator detection system in a batch mode, to detect second anomaly data. A third anomaly is detected using an anomaly detection rule. The threat indictor system processes the first anomaly data, the second anomaly data, and the third anomaly data using a threat indicator model to identify a threat indicator associated with a potential security threat to the computer network.
Methods and devices are disclosed herein to facilitate the detection of Domain Name System (DNS) exfiltration attacks. In some examples, a DNS request is used to generate a tokenized vector that corresponds to the DNS request, features of the DNS request, and aggregated features calculated over a sliding window representative of a recent history of events between a particular source and domain. The tokenized vector is input into a neural network to generate a probability score indicating a likelihood that the current DNS request corresponds to a DNS exfiltration. A graphical user interface is generated to display an indication of the probability score for the current DNS request.
Various implementations of the present application set forth a method comprising generating, three-dimensional data and two-dimensional data representing a physical space that includes a real-world asset, generating an adaptable three-dimensional (3D) representation of the physical space based on the two-dimensional and three-dimensional data, where the adaptable 3D representation includes a plurality of coordinates representing different positions in 3D coordinate space corresponding to the physical space, transforming the adaptable 3D representation into geometry data comprising a set of vertices, faces comprising edges between pairs of vertices, and texture data, transmitting the geometry data to a remote device, wherein the remote device, constructs, based on the geometry data, the adaptable 3D representation of the physical space for display at a location of the remote device in a remote environment, and modifies, based on an input, at least one of a dimension or a position of the adaptable 3D representation.
G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
G06T 7/521 - Récupération de la profondeur ou de la forme à partir de la télémétrie laser, p. ex. par interférométrieRécupération de la profondeur ou de la forme à partir de la projection de lumière structurée
The present disclosure provides techniques for AID generation for enhanced data privacy (EDP) operations. An AP provides a first communication indicating that the AP supports a randomized MAC address rotation management protocol. The AP establishes a communications link between the AP and a STA, where establishing the communications link comprises assigning the STA to an EDP group. The AP generates a list of N AIDs for the STA, each of the N AIDs to be used in a corresponding epoch of N epochs associated with the EDP group. The AP transmits, to the STA in a protected wireless frame, information indicating the list of N AIDs for the STA. The AP maintains the communications link with the STA based at least in part on the timing information for randomized MAC address rotation for the EDP group, and including using each AID in the list of N AIDs during corresponding epochs.
A meeting server provides, to one or more participants of an online meeting, an invitation to join the online meeting. The invitation including an option to request one or more accommodations for the online meeting. The meeting server obtains, from a participant of the one or more participants, a request for an accommodation, of the one or more accommodations, during the online meeting. The meeting server performs one or more actions associated with the request for the accommodation.
Systems, methods, and computer-readable media are disclosed for validating multiple paths used for routing network traffic in a network. In one aspect, a network controller can identify one or more intermediate nodes on each of multiple paths in a network, wherein the multiple paths begin at a first network node and end at a last network node. The network controller can further generate a data packet with a label at the first network node, forward the test data packet from the first network node, along each of the one or more intermediate nodes, to the last network node, and perform a data plane validation process for validating packet forwarding from the first network node to the last network node based on the label(s) by determining if a number of the multiple paths equals to a number of packets received at the last network node.
A system of one embodiment provides for efficient grid-estimation of spherical geo-probability function. The system includes a memory and a processor. The system accesses data, wherein the data includes training points and each training point includes a latitude value and a longitude value. The system also generates one or more grid points around each training point in the data. The system calculates a probability value for each grid point in the plurality of grid points using a probability density function. The system also combines each grid point into a geo-grid. The systems stores the geo-grid. In some embodiments, the system combines each grid point into a geo-grid by adding a probability value of a first grid point to a probability value of second grid point.
Techniques for tunneling Layer 2 ethernet frames over a connection tunnel using the MASQUE protocol are described herein. The MASQUE protocol may be extended to include a new entity, configured to proxy ethernet frames using a MASQUE proxy connection, and an associated CONNECT method, CONNECT-ETH. Using the extended MASQUE protocol, an Ethernet over MASQUE (EoMASQUE) tunnel may then be established between various networks that are remote from one another and connected to the internet. An EoMASQUE tunnel, established between separate remote client premises, and/or between a remote client premise and an enterprise premise, may tunnel ethernet packets between the endpoints. Additionally, a first EoMASQUE tunnel, established between a first client router provisioned in a first remote client premise and an EoMASQUE proxy node, and a second EoMASQUE tunnel, established between a second client premise and the EoMASQUE proxy node, may tunnel ethernet packets between the first and second client premise.
H04L 61/103 - Correspondance entre adresses de types différents à travers les couches réseau, p. ex. résolution d’adresse de la couche réseau dans la couche physique ou protocole de résolution d'adresse [ARP]
H04L 61/4511 - Répertoires de réseauCorrespondance nom-adresse en utilisant des répertoires normalisésRépertoires de réseauCorrespondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
H04L 67/101 - Sélection du serveur pour la répartition de charge basée sur les conditions du réseau
H04L 67/1012 - Sélection du serveur pour la répartition de charge basée sur la conformité des exigences ou des conditions avec les ressources de serveur disponibles
H04L 67/141 - Configuration des sessions d'application
H04L 67/562 - Courtage des services de mandataires
100.
IP PERFORMANCE MEASUREMENT EXTENSION FOR FASTER CONVERGENCE WITH MULTIHOMING
A system and method are provided for faster convergence with multihoming using internet protocol (IP) performance measurement (PM) sessions to report, to a transmitting provider edge (PE), a state of health of a connection between a multihomed node and a receiving (PE). The state of health can be the liveness of the connection. The receiving PE locally monitors the state of health of its connection to the node, and encodes information of the state of health in a field of the PM session messages sent to the transmitting PE. For example, while the PM session messages indicate the connection is live, traffic from the transmitting PE to the node is routed through the receiving PE. Upon the PM session messages indicating the connection is no longer live, the transmitting PE instead routes traffic to the node through another receiving PE with which the node is multihomed.
