Intel Corporation

Apple Inc.

Intel University

Intel IP Corporation

Satish Chandra Jha

Rath Vannithamby

Ali Taha Koc

Kathiravetpillai Sivanesan

Ned M Smith

Francesc Guim Bernat

Kshitij Arun Doshi

Srikathyayani Srikanteswara

Jing Zhu

Christian Maciocco

Yujian Zhang

Qian Li

Marta Martinez Tarradell

Nageen Himayat

Ignacio Javier Alvarez

Geng Wu

Hassnaa Moustafa

Puneet K Jain

Youn Hyoung Heo

Hyung-Nam Choi

Tao Wu

Hong He

Yushu Zhang

Dae Won Lee

Gang Xiong

Alexei Vladimirovich Davydov

Mo-Han Fong

Jie Cui

Debdeep Chatterjee

Joonyoung Cho

Yongjun Kwak

Sergey Panteleev

Joey Chou

Markus Dominik Mueck

Rui Huang

Bharat Shrestha

Candy Yiu

Alexander Sasha Sirotkin

Richard Charles Burbidge

Gregory Vladimirovich Morozov

Manoj R Sastry

Yi Guo

Jeongho Jeon

Ren Wang

S M Iftekharul Alam

Maruti Gupta

Mohammad Mamunur Rashid

Vesh Raj Sharma Banjade

Kuilin Clark Chen

Yi Zhang

Gabriel Arrobo Vidal

Yaser M Fouad

Zongrui Ding

Venkatesan Nallampatti Ekambaram

Maruti Gupta Hyde

Sangeetha L Bangolae

Lu Lu

Dawei Ying

Eve M Schooler

Hassan Ghozlan

Joonbeom Kim

Guangjie Li

Ravikumar Balakrishnan

Maria E Ramirez Loaiza

Arvind Merwaday

Liuyang L Yang

David Israel Gonzalez Aguirre

Alexander Bachmutsky

Sridhar G Sharma

Leonardo Gomes Baltar

Jeffrey Sedayao

Richard Dorrance

Xiaoyun May Wu

Deepak Dasalukunte

Ana Lucia Pinheiro

Jessica C McCarthy

Ignacio J Alvarez Martinez

Seau Sian Lim

Andrey Chervyakov

Honglei Miao

Anthony Lee

Yizhi Yao

Hua Li

Marcio Rogerio Juliato

Robert Zaus

Farid Adrangi

Jaemin Han

Javier Felip Leon

Sebastian Schoenberg

Avik Sengupta

Marcos Emanuel Carranza

Yuhan Zhou

Mona Vij

David Arditti Ilitzky

Chang Hong Shan

Cesar Martinez-Spessot

Maria Soledad Elli

Mateo Guzman

Marcin Spoczynski

Sindhu Pandian

A system is disclosed for quarantining and recovery of a network after an outage or in advance of a potential outage. Unaffected network slices are isolated and recovery is initiated by quarantine physical and virtual network functions. An AI model is trained based on recent events detected by sensors disposed throughout the network to determine whether to quarantine network slices, move services to unaffected network slices, or initiate recovery. Once the network is stabilized, resources that are specifically allocated for recovery and services are released and the traffic moved back to the recovered network slices.

Quarantine control network in a 5G RAN for coordinated multi-layer resiliency of network slice resources

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

Maneuver Coordination Services (MCS) may be used in various implementations of vehicular networks. Emergency Group Maneuver Coordination (EGMC) may be used for detected unexpected safety-critical situations (USCS) on the road. EGMC provides cooperative maneuver coordination among a group of vehicles to ensure safer collective actions in the case of USCS. An MCS and EGMC may utilize a Maneuver Coordination Message (MCM) based on procedures for the Generation and Transmission of MCM with reduced communication overhead.

Maneuver coordination service in vehicular networks

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

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

The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to Vulnerable Road User (VRU) basic services (VBS) of a VRU ITS Station (ITS-S). Implementations of how the VBS is arranged within the facilities layer of an ITS-S, different conditions for VRU Awareness Message (VAM) dissemination, and format and coding rules of the VAM generation.

Vulnerable road user basic service communication protocols framework and dynamic states

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

The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to service dissemination basic services (SDBS) and/or collective perception service (CPS) of an ITS Station (ITS-S). Implementations of how the SDBS and/or CPS is arranged within the facilities layer of an ITS-S, different conditions for service dissemination messages (SDMs) and/or collective perception message (CPM) dissemination, and format and coding rules of the SDM/CPS generation are provided.

Collective perception service enhancements in intelligent transport systems

Growing community of inventors

Hillsboro, OR, United States of America

Satish Chandra Jha