Intel Corporation

Timothy Verrall

Francesc Guim Bernat

Ned M Smith

Karthik Kumar

Kshitij Arun Doshi

Thomas Willhalm

Suraj Prabhakaran

John Joseph Browne

Tarun Viswanathan

Maryam Tahhan

Mark A Schmisseur

Kapil Sood

Eoin Walsh

Ignacio Astilleros Diez

Patrick G Kutch

Brinda Ganesh

Manish Dave

Rajesh Gadiyar

Rita H Wouhaybi

Andrew J Herdrich

Dennis M Morgan

Tomasz Kantecki

Michael J McGrath

Steven J Birkel

Mrigank Shekhar

Christopher MacNamara

Sean Harte

Jonathan Kenny

Uzair Qureshi

Kevin Devey

Rajesh Poornachandran

Tobias Max Kohlenberg

Susanne M Balle

Omer Ben-Shalom

Chris MacNamara

Mubashir A Mian

Keith L Shippy

Ramanathan Sethuraman

Eran Birk

Trevor Cooper

Damien Power

Alexander Vul

Felipe Pastor Beneyto

Marcel Cornu

Steve Devereux

Rodney B Rubert

Katalin Klara Bartfai-Walcott

Alexander Bachmutsky

Evan Custodio

Alan D Ross

Nilesh K Jain

Bassam N Coury

Weigang Li

Sanjay Rungta

Rashmin N Patel

Monica Kenguva

Niall Power

Benjamin Graniello

Ravi Iyer

Shobhi Jain

Rory Browne

Deepak S

Emma Louise Foley

Mike Bursell

Ben McCahill

Palaniappan Ramanathan

Kannan Babu Ramia

Alex Vul

Steven Briscoe

Kevin Bohan

Peter Mangan

Wojciech Andralojc

Roy Beiser

Itzhak Eizenberg

Alex Rentzis

Various approaches for implementing multi-tenant data protection are described. In an edge computing system deployment, a system includes memory and processing circuitry coupled to the memory. The processing circuitry is configured to obtain a workflow execution plan that includes workload metadata defining a plurality of workloads associated with a plurality of edge service instances executing respectively on one or more edge computing devices. The workload metadata is translated to obtain workload configuration information for the plurality of workloads. The workload configuration information identifies a plurality of memory access configurations and service authorizations identifying at least one edge service instance authorized to access one or more of the memory access configurations. The memory is partitioned into a plurality of shared memory regions using the memory access configurations. A memory access request for accessing one of the shared memory regions is processed based on the service authorizations.

Multi-tenant data protection in edge computing environments

A computing apparatus, including: a hardware platform; and an interworking broker function (IBF) hosted on the hardware platform, the IBF including a translation driver (TD) associated with a legacy network appliance lacking native interoperability with an orchestrator, the IBF configured to: receive from the orchestrator a network function provisioning or configuration command for the legacy network appliance; operate the TD to translate the command to a format consumable by the legacy network appliance; and forward the command to the legacy network appliance.

Interworking of legacy appliances in virtualized networks

Systems and techniques for intelligent data forwarding in edge networks are described herein. A request may be received from an edge user device for a service via a first endpoint. A time value may be calculated using a timestamp of the request. Motion characteristics may be determined for the edge user device using the time value. A response to the request may be transmitted to a second endpoint based on the motion characteristics.

Intelligent data forwarding in edge networks

Methods and apparatus for scale out hardware-assisted tracing schemes for distributed and scale-out applications. In connection with execution of one or more applications using a distributed processing environment including multiple compute nodes, telemetry and tracing data are obtained using hardware-based logic on the compute nodes. Processes associated with applications are identified, as well as the compute nodes on which instances of the processes are executed. Process instances are associated with process application space identifiers (PASIDs), while processes used for an application are associating with a global group identifier (GGID) that serves as an application ID. The PASIDs and GGIDs are used to store telemetry and/or tracing data on the compute nodes and/or forward such data to a tracing server in a manner that enables telemetry and/or tracing data to be aggregated on an application basis. Telemetry and/or tracing data may be obtained from processors on the compute nodes, and (optionally) additional elements such as network interface controllers (NICs). Tracing data may also be obtained from switches used for forwarding data between processes.

Hardware-assisted tracing schemes for distributed and scale-out applications

Various aspects of methods, systems, and use cases include coordinating actions at an edge device based on power production in a distributed edge computing environment. A method may include identifying a long-term service level agreement (SLA) for a component of an edge device, and determining a list of resources related to the component using the long-term SLA. The method may include scheduling a task for the component based on the long-term SLA, a current battery level at the edge device, a current energy harvest rate at the edge device, or an amount of power required to complete the task. A resource of the list of resources may be used to initiate the task, such as according to the scheduling.

Adaptive power management for edge device

Examples described herein relate to an apparatus that includes a memory and at least one processor where the at least one processor is to receive configuration to gather performance data for a function from one or more platforms and during execution of the function, collect performance data for the function and store the performance data after termination of execution of the function. Some examples include an interface coupled to the at least one processor and the interface is to receive one or more of: an identifier of a function, resources to be tracked as part of function execution, list of devices to be tracked as part of function execution, type of monitoring of function execution, or meta-data to identify when the function is complete. Performance data can be accessed to determine performance of multiple executions of the short-lived function.

Performance monitoring for short-lived functions

Methods and systems that allow a user to see the people or groups who have access to files that are maintained by a plurality of cloud content sharing services. In particular, the user may see what specific party has access to each particular file or directory, regardless of multiple cloud content sharing services involved. Moreover, a user interface and exposed application program interface allows the user to manipulate the permissions, e.g., granting access, to another person or group, to a file or directory. The user interface may also allow the user to terminate access to the file or directory for a person or group. The user's action to change a permission may be effected independently of the particular cloud content sharing service.

Unifying interface for cloud content sharing services

Example edge gateway circuitry to schedule service requests in a network computing system includes: gateway-level hardware queue manager circuitry to: parse the service requests based on service parameters in the service requests; and schedule the service requests in a queue based on the service parameters, the service requests received from client devices; and hardware queue manager communication interface circuitry to send ones of the service requests from the queue to rack-level hardware queue manager circuitry in a physical rack, the ones of the service requests corresponding to functions as a service provided by resources in the physical rack.

Methods and apparatus to schedule service requests in a network computing system using hardware queue managers

Technologies for accelerated key caching in an edge hierarchy include multiple edge appliance devices organized in tiers. An edge appliance device receives a request for a key, such as a private key. The edge appliance device determines whether the key is included in a local key cache and, if not, requests the key from an edge appliance device included in an inner tier of the edge hierarchy. The edge appliance device may request the key from an edge appliance device included in a peer tier of the edge hierarchy. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys in the key cache for eviction. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys for pre-fetching. Those functions of the edge appliance device may be performed by an accelerator such as an FPGA. Other embodiments are described and claimed.

Technologies for accelerated hierarchical key caching in edge systems

Systems and methods may be used to provide neutral host edge services in an edge network. An example method may include generating a virtual machine for a communication service provider at a compute device. The method may include receiving a user packet originated at a user device associated with the communication service provider and identifying dynamic route information related to the user packet using the virtual machine corresponding to the communication service provider. Data may be output corresponding to the user packet based on the dynamic route information.

Neutral host edge services

Technologies for providing selective offload of execution of an application to the edge include a device that includes circuitry to determine whether a section of an application to be executed by the device is available to be offloaded. Additionally, the circuitry is to determine one or more characteristics of an edge resource available to execute the section. Further, the circuitry is to determine, as a function of the one or more characteristics and a target performance objective associated with the section, whether to offload the section to the edge resource and offload, in response to a determination to offload the section, the section to the edge resource.

Technologies for providing selective offload of execution to the edge

Methods, apparatus, systems, and articles of manufacture are disclosed to aggregate telemetry data in an edge environment. An example apparatus includes at least one processor, and memory including instructions that, when executed, cause the at least one processor to at least generate a composition for an edge service in the edge environment, the composition representative of a first interface to obtain the telemetry data, the telemetry data associated with resources of the edge service and including a performance metric, generate a resource object based on the performance metric, generate a telemetry object based on the performance metric, and generate a telemetry executable based on the composition, the composition including at least one of the resource object or the telemetry object, the telemetry executable to generate the telemetry data in response to the edge service executing a computing task distributed to the edge service based on the telemetry data.

Methods and apparatus to aggregate telemetry data in an edge environment

Methods, apparatus, systems and articles of manufacture for re-use of a container in an edge computing environment are disclosed. An example method includes detecting that a container executed at an edge node of a cloud computing environment is to be cleaned, deleting user data from the container, the deletion of the user data performed without deleting the container from the memory of the edge node, restoring settings of the container to a default state; and storing information identifying the container, the information including a flavor of the container, the storing of the information to enable the container to be re-used by a subsequent requestor.

Methods and apparatus for re-use of a container in an edge computing environment

There is disclosed in one example an application-specific integrated circuit (ASIC), including: an artificial intelligence (AI) circuit; and circuitry to: identify a flow, the flow including traffic diverted from a core cloud service of a network to be serviced by an edge node closer to an edge of the network than to the core of the network; receive telemetry related to the flow, the telemetry including fine-grained and flow-level network monitoring data for the flow; operate the AI circuit to predict, from the telemetry, a future service-level demand for the edge node; and cause a service parameter of the edge node to be tuned according to the prediction.

Scalable edge computing

Methods, apparatus, systems and articles of manufacture are disclosed to schedule workloads based on secure edge to device telemetry by calculating a difference between a first telemetric data received from a first hardware device and an operating parameter and computing an adjustment for a second hardware device based on the difference between the first telemetric data and the operating parameter.

Methods and apparatus to schedule workloads based on secure edge to device telemetry

Growing community of inventors

Pleasant Hill, CA, United States of America

Timothy Verrall