Intel Corporation

Tahoe Research, Ltd.

Apple Inc.

Christian Maciocco

Tsung-Yuan Charles Tai

Ren Wang

Kshitij Arun Doshi

Francesc Guim Bernat

Shlomo Ovadia

Rath Vannithamby

Nageen Himayat

Satish Chandra Jha

Srikathyayani Srikanteswara

S M Iftekharul Alam

Kristoffer Fleming

Ned M Smith

Hassnaa Moustafa

Jr-Shian Tsai

Liuyang L Yang

Eve M Schooler

Sanjay Bakshi

Kapil Sood

Richard A Uhlig

Sebastian Schoenberg

Shilpa Talwar

Kathiravetpillai Sivanesan

Alexander W Min

Vallabhajosyula S Somayazulu

Maruti Gupta Hyde

Christopher J Hughes

Rajesh M Sankaran

Andrew J Herdrich

Ohad Falik

Yen-Cheng Liu

Ben-Zion Friedman

Hang T Nguyen

Herbert H Hum

Alexander Bachmutsky

Vijay Sarathi Kesavan

Jong Soo Park

Carlos Cordeiro

Emily H Qi

David J Harriman

Paul S Diefenbaugh

Patrick L Connor

Yang-Seok Choi

Ignacio Javier Alvarez

Xue Yang

Boris Ginzburg

Prashant R Chandra

Nadav Shulman

Lakshman Krishnamurthy

Russell Jerome Fenger

Sameh Gobriel

Vesh Raj Sharma Banjade

Ahmad A Samih

Tsung-Yuan Charlie Tai

Namakkal N Venkatesan

Rajendra S Yavatkar

David John Zage

Zeshan A Chishti

Sanjeev Jain

Jeffrey R Jackson

Kuilin Clark Chen

Mesut A Ergin

Malini Krishnan Bhandaru

Aamer Jaleel

Jessica C McCarthy

Yunhong Jiang

Mona Vij

Manav Mishra

Jeffrey Sedayao

Eric R Delano

Yi Zhang

Adrian C Moga

Nrupal R Jani

Sung Ho Lee

Shrikant M Shah

David Ott

Meiyuan Zhao

David E Cohen

Arvind Merwaday

James W Alexander

Anthony George LaMarca

Kerstin Johnsson

Gabriel Arrobo Vidal

Rajeev D Muralidhar

Jeffrey R Foerster

Iosif Gasparakis

Ravikumar Balakrishnan

Srihari Makineni

Michael J Espig

Arun Raghunath

Harinarayanan Seshadri

Scott D Hahn

Raj S Yavatkar

Jaideep Moses

John R Fastabend

Bruce Richardson

Eric K Mann

Myron Hattig

Ajay G Gupta

Jingwen Bai

Methods, apparatus, systems, and articles of manufacture are disclosed to improve mobile edge platform resiliency. An example apparatus includes memory, instructions, and processor circuitry to execute the instructions to initiate a search for one of an access point or a cluster head at a first time, in response to detection of the cluster head, initiate an intra-cluster mobile edge platform (MEP) mutual authentication associated with the cluster head, cause transmission of historical activity data to at least one MEP associated with the cluster head, and cause storage of an authentication metric in a secure storage, the authentication metric based on historical connectivity data.

Methods, systems, articles of manufacture and apparatus to improve mobile edge platform resiliency

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

A non-transitory computer-readable storage medium stores instructions to configure a base station for user equipment (UE) authentication in a wireless network and to cause the base station to perform an operation comprising decoding configuration signaling received from a PHY security function (PSF) of the wireless network. The configuration signaling includes a request for collection of a plurality of signal samples from the UE, the UE authenticated based on successful completion of a first authentication process. A response message is encoded for transmission to the PSF. The response message includes the plurality of UE signal samples. A trained machine learning model received from the PSF is decoded. The trained machine learning model associates the authenticated UE with an RF signature of the UE. The RF signature is based on the plurality of signal samples. A second authentication process of the UE is performed based on the trained model.

Adaptive and hierarchical network authentication framework

The present disclosure relates to a system for use in a wireless network, the system including: a processor configured to determine a performance parameter representative of a performance of a model of radio resource management, the model operating on a radio access network environment; and a radio resource manager configured to perform radio resource management dependent on the performance parameter.

Radio resource model management in a wireless network

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

An apparatus and system to mitigate non-genuine handovers are described. The handovers include handovers based on fake measurements and handovers to malicious cells. To mitigate these, a mitigation procedure is initiated when excessive handovers are detected. Location information obtained from the UE, estimation of PHY layer properties by the serving and/or target cell, or AI modeling of the best serving cell at the UE location is used to determine whether the handover is valid. If not, the handover is canceled and the UE is stopped from initiating new handovers for a specified time, the UE may be instructed to perform re-authentication with the network, and/or the serving cell recommends to the network authentication entity to revoke the UE authentication. To ensure that the target cell is legitimate, an AI model is used to classify the target cell as known/unknown and the result sent to the network in NAS signaling.

Physical layer techniques to mitigate the handover process vulnerabilities

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

Disclosed herein are systems and methods for peer-assisted safety models for autonomous and assisted-driving vehicles. In an embodiment, a safety-model service receives a safety-model request for a safety model from a target vehicle. The safety-model service identifies, responsive to receiving the safety-model request, one or more source vehicles as safety-model input sources. The safety-model service receives safety-model data associated with the identified one or more source vehicles. The safety-model service generates, based on the safety-model request and the received safety-model data, a target-vehicle safety model for the target vehicle. The safety-model service transmits the target-vehicle safety model to the target vehicle for use by the target vehicle.

Systems and methods for brokering peer-assisted safety models for autonomous and assisted-driving vehicles

An apparatus for an S-BS includes processing circuitry configured to decode configuration signaling from a plurality of S-UEs. The configuration signaling indicates an interference level at each of the plurality of S-UEs from transmissions of an M-BS. An S-UE is selected based on a comparison of the interference level at each S-UE with an interference threshold of each S-UE. Control signaling is encoded for transmission to the selected S-UE via a small cell access (S-AC) communication link. The control signaling is transmitted during the reception of downlink data from the M-BS via a primary backhaul communication link.

Full duplex communications in wireless networks

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

System and techniques for information centric network unstructured data carrier are described herein. A user plane function (UPF) node receives an initiation for a packet data unit (PDU) session of user equipment (UE). Here, the initiation includes an indication for an ICN session and a PDU session identification (ID). The PDU session may then map the PDU session to the PDU session ID in an ICN routing data structure. Here, the ICN routing data structure is one or both of the pending interest table (PIT) or the forwarding interest base (FIB) of the UPF node. An ICN packet (interest or data packet) may be from the UE contained within a PDU on from the PDU session that conforms to an unstructured-data classification as defined by a 3GPP 5G family of standards. The ICN packet is extracted from the PDU and routed in accordance with the ICN routing data structure.

Information centric network unstructured data carrier

An apparatus and system to provide separate network slices for security events are described. A dedicated secure network slice is provided for PDP data from a UE. The network slice is used for detecting security issues and sending security-related information to clients. The communications in the dedicated network slice are associated with a special PDP context used by the UE to interface with the network slice. Once the UE has detected a security issue or has been notified of the security issue on the network or remote servers, the UE uses a special PDP service, and is able to stop uplink/downlink channels, close running applications and enter into a safe mode, cut off connections to the networks, and try to determine alternate available connectivity.

Separate network slicing for security events propagation across layers on special packet data protocol context

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

Growing community of inventors

Portland, OR, United States of America

Christian Maciocco