Intel Corporation

Apple Inc.

S M Iftekharul Alam

Satish Chandra Jha

Ned M Smith

Kuilin Clark Chen

Yi Zhang

Kathiravetpillai Sivanesan

Francesc Guim Bernat

Vesh Raj Sharma Banjade

Kshitij Arun Doshi

Srikathyayani Srikanteswara

Gabriel Arrobo Vidal

Christian Maciocco

Zongrui Ding

Venkatesan Nallampatti Ekambaram

Stepan Karpenko

Nageen Himayat

Ignacio Javier Alvarez

Eve M Schooler

Sridhar G Sharma

Ravikumar Balakrishnan

Maria E Ramirez Loaiza

Arvind Merwaday

Hassnaa Moustafa

David Israel Gonzalez Aguirre

Alexander Bachmutsky

Rath Vannithamby

Mohammad Mamunur Rashid

Maruti Gupta Hyde

Ching-Yu Liao

Jeffrey Sedayao

Richard Dorrance

Deepak Dasalukunte

Qian Li

Liuyang L Yang

Lu Lu

Yaser M Fouad

Jessica C McCarthy

Marcin Spoczynski

Ignacio J Alvarez Martinez

Ranganath Krishnan

Hao Feng

Javier Felip Leon

Sebastian Schoenberg

Jason Martin

Mona Vij

Marcos Emanuel Carranza

Michael Paulitsch

Florian Geissler

Maria Soledad Elli

Cesar Martinez-Spessot

Mateo Guzman

Rafael Rosales

Nilesh Amar Ahuja

Sindhu Pandian

Dario Oliver

Avinash Kumar

Lakshmi N Talluru

Mehnaz Rahman

Amar Srivastava

Xiaoyun May Wu

Methods, apparatus, systems, and articles of manufacture are disclosed for data resiliency in an edge network environment. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to at least one of execute and/or instantiate the instructions to generate spectrum metadata based on spectrum data, determine a resiliency operation based on one or more resiliency requirements, generate a resiliency policy based on at least one of the resiliency operation or the one or more resiliency requirements, generate a resiliency operation map based on at least one of the resiliency policy or first identifiers of respective workloads associated with the network environment, the first identifiers including a second identifier, and, in response to identifying a FAFO event associated with the second identifier, execute the resiliency operation based on mapping the second identifier to the resiliency operation in the resiliency operation map.

Systems, apparatus, and methods for data resiliency in an edge network environment

A digital twin model is generated for physical nodes of an edge network. The digital twin model includes a digital twin for a physical node of the physical nodes. An error is identified of the physical node or the digital twin for the physical node. The digital twin model is updated to halt communication with the physical node or the digital twin of the physical node. A path is created to another physical node or a digital twin of the another physical node in the digital twin model.

Digital twin framework for next generation networks

Methods, apparatus, systems, and articles of manufacture are disclosed to increase resiliency in self-healing mechanisms. At least one non-transitory machine-readable medium comprises instructions that, when executed, cause at least one processor to at least partition computational resources of a first host into a primary partition and a shadow partition, the primary partition to communicate with a second host, apply a fix for the primary partition, determine if the primary partition can communicate with the second host during the application of the fix, cause, in response to the determination that the primary partition cannot communicate with the second host during the application of the fix, the shadow partition to communicate with the second host; and transfer communication with the second host from the shadow partition to the primary partition, the transfer in response to a determination that the application of the fix is complete.

Methods and apparatus to increase resiliency in self-healing mechanisms

Various aspects of methods, systems, and use cases include security-based orchestration. A method may include evaluating, within a secure environment of an untrusted device, a preamble to determine a set of security requirements. The method may include, providing, to an attestation server, an indication of security parameters for services of the untrusted device corresponding to security requirements of the set of security requirements, and in response to receiving a confirmation from the attestation server, providing a request to the untrusted device outside the secure environment to generate a trusted domain including the services.

Network supported low latency security-based orchestration

Systems and techniques for cross-layer automated fault tracking and anomaly detection are described herein. Anomaly data may be obtained from a plurality of layers of a network. Elements of the anomaly data may be identified that correspond to a data flow of an application executing on the network. An artificial intelligence model may be trained using the elements of the anomaly data to generate an impact score for the application. The impact score may be generated for the application by evaluating current network metrics using the artificial intelligence model. An operational component of the network may be modified based on the impact score.

Cross-layer automated fault tracking and anomaly detection

A computing node includes network interface circuitry and processing circuitry. The processing circuitry assigns available computing resources to a plurality of slice contexts. Each slice context of the plurality includes resource allocations of the available computing resources associated with multiple communication networks. A first portion of the resource allocations is designated as dedicated resources and a second, remaining portion is designated as shared resources. A FAFO event associated with a workload is detected. The workload executes on a network slice instance (NSI) associated with a slice context of a subset of slice contexts. The configuration of the NSI is restored to a pre-FAFO event state based on reconfiguring one or both of the dedicated resources or the shared resources of the slice context based on the resource allocations of at least a second slice context in the subset of slice contexts.

End-to-end network slicing (ENS) from ran to core network for next generation (NG) communications

System and techniques for geographic routing are described herein. A node receives a data packet that includes map data, a sequence of geographic areas to a requestor, and a target geographic area. The node may then determine that it is within the target geographic area and start a transmit timer based on a next-hop geographic area. Here, the next-hop geographic area is determined from the sequence of geographic areas in the data packet. The node may then counts how many other nodes from the geographic area sent data packets while the transmit timer is running. When the transmit timer expires, the node may transmit a modified data packet when the number of data packets is less than a predefined threshold. Here, the modified data packet is the data packet updated to include local map data and the next-hop geographic area.

Geographic routing

Various aspects of methods, systems, and use cases include en-route computing coordination. A method may include receiving a packet including a compute task and context information, identifying a destination node for the packet, and determining a route for the packet to the destination node. The route may include an intermediary node determined based on the context information and available resources at the intermediary node to execute the compute task of the packet at the intermediary node. The method may include forwarding the packet to a next device along the route.

Software defined networking with en-route computing

System and techniques for storage node recruitment in an information centric network (ICN) are described herein. An ICN node receives a storage interest packet that includes an indication differentiating the storage interest from other ICN interests. The ICN node forwards the storage interest packet and receives a storage data packet in response. Here, the storage data packet includes an indication that the storage data packet is not to be cached along with node information for a node that created the storage data packet. The ICN node may then transmit the storage data packet in accordance with a pending interest table (PIT) entry corresponding to the storage interest packet.

Storage node recruitment in an information centric network

A computing node includes interface circuitry and processing circuitry. To implement a spectrum harvesting entity in a wireless network configured for crowdsource-based unlicensed spectrum harvesting, the processing circuitry is configured to select a set of crowdsourcing nodes from a plurality of crowdsourcing nodes available in the wireless network. A plurality of spectrum occupancy reports (SORs) is received from the set of crowdsourcing. Each of the plurality of SORs indicates a channel occupancy status of a communication channel in the unlicensed spectrum sensed by a corresponding crowdsourcing node of the set and geolocation associated with the corresponding crowdsourcing node. A spectrum occupancy map of the unlicensed spectrum is generated based on the channel occupancy status and the geolocation provided in the plurality of SORs by each crowdsourcing node of the set of crowdsourcing nodes.

Unlicensed spectrum harvesting with collaborative spectrum sensing in next generation networks

Systems and techniques for mobility-as-a-service for user experience are described herein. An orchestration log may be maintained that includes current orchestration data. An orchestration backup record may be generated that includes alternate MaaS nodes on the MaaS network. It may be determined that connectivity is lost to a first orchestration container hosted by a first MaaS node. An orchestration container is generated using the orchestration log to maintain orchestration functionality. An available second MaaS node is identified from the alternate MaaS nodes. The orchestration container may be transferred to the second MaaS node.

Mobility-as-a-service for user experience

Disclosed herein are systems and methods for vehicle-occupancy-based and user-preference-based smart routing, and autonomous volumetric-occupancy measurement. In an embodiment, a system is configured to receive from a user device associated with a user, a routing-options request for routing options between two locations, and to responsively identify one or more routing options between the two locations based at least in part on occupancy data for a vehicle that would be utilized for at least a portion of at least one of the identified routing options. The occupancy data is based on an output of an automated occupancy-measurement system onboard the vehicle. The system is also configured to provide the one or more identified routing options to the user device. In some embodiments, the occupancy data is obtained using volumetric-occupancy measurement. Some embodiments relate to volumetric-occupancy measurement conducted by autonomous mesh nodes.

Systems and methods for vehicle-occupancy-based and user-preference-based smart routing and autonomous volumetric-occupancy measurement

Various systems and methods for improving connectivity of a Mobility-as-a-Service (MaaS) node are described herein, including categorizing MaaS communication traffic of a MaaS node into different levels of priority and controlling duplication or repetition of the MaaS communication traffic using the categorized level of priority of the MaaS communication traffic.

Always-on mobility-as-a-service connectivity

A resource management framework may be used to improve performance of dominant and non-dominant resources for edge multi-tenant applications. The resource management framework may include an admission control mechanism, which may be used to balance disproportionate resource allocations by controlling allocation of unconstrained resources proportional to the requested dominant resources based on resource availability. The admission control mechanism may provide ongoing monitoring of dominant and non-dominant resource utilization, such as using a hybrid centralized-distributed telemetry collection approach. The resource management framework may also include a lightweight resource monitoring and policy enforcement mechanism on distributed networking elements to reduce or eliminate the exploitations of non-dominant resources.

Nondominant resource management for edge multi-tenant applications

V2X trusted agents provide technical solutions for technical problems facing falsely reported locations of connected vehicles within V2X systems. These trusted agents (e.g., trusted members) may be used to detect an abrupt physical attenuation of a wireless signal and determine whether the attenuation was caused by signal occlusion caused by the presence of an untrusted vehicle or other untrusted object. When the untrusted vehicle is sending a message received by trusted agents, these temporary occlusions allow trusted members to collaboratively estimate the positions of untrusted vehicles in the shared network, and to detect misbehavior by associating the untrusted vehicle with reported positions. Trusted agents may also be used to pinpoint specific mobile targets. Information about one or more untrusted vehicles may be aggregated and distributed as a service.

Pathloss drop trusted agent misbehavior detection

Growing community of inventors

Hillsboro, OR, United States of America

S M Iftekharul Alam