Intel Corporation

Rashmin N Patel

Francesc Guim Bernat

Monica Kenguva

Andrew J Herdrich

Ned M Smith

Karthik Kumar

Brinda Ganesh

Alexander Vul

Edwin Verplanke

Felipe Pastor Beneyto

Kshitij Arun Doshi

Suraj Prabhakaran

Patrick G Kutch

Petar Torre

Patrick Bohan

Ravi L Sahita

Tsung-Yuan Charles Tai

Ren Wang

Alexander W Min

Jr-Shian Tsai

Timothy Verrall

Scott P Dubal

Stephen T Palermo

Mesut A Ergin

Nilesh K Jain

Weigang Li

Changzheng Wei

Junyuan Wang

Jun Nakajima

Danny Yigang Zhou

Benjamin Graniello

Hari K Tadepalli

An architecture to perform resource management among multiple network nodes and associated resources is disclosed. Example resource management techniques include those relating to: proactive reservation of edge computing resources; deadline-driven resource allocation; speculative edge QoS pre-allocation; and automatic QoS migration across edge computing nodes. In a specific example, a technique for service migration includes: identifying a service operated with computing resources in an edge computing system, involving computing capabilities for a connected edge device with an identified service level; identifying a mobility condition for the service, based on a change in network connectivity with the connected edge device; and performing a migration of the service to another edge computing system based on the identified mobility condition, to enable the service to be continued at the second edge computing apparatus to provide computing capabilities for the connected edge device with the identified service level.

Quality of service (QoS) management in edge computing environments

A device of a service coordinating entity includes communications circuitry to communicate with a plurality of access networks via a corresponding plurality of network function virtualization (NFV) instances, processing circuitry, and a memory device. The processing circuitry is to perform operations to monitor stored performance metrics for the plurality of NFV instances. Each of the NFV instances is instantiated by a corresponding scheduler of a plurality of schedulers on a virtualization infrastructure of the service coordinating entity. A plurality of stored threshold metrics is retrieved, indicating a desired level for each of the plurality of performance metrics. A threshold condition is detected for at least one of the performance metrics for an NF V instance of the plurality of NFV instances, based on the retrieved plurality of threshold metrics. A hardware resource used by the NFV instance to communicate with an access network is adjusted based on the detected threshold condition.

Dynamic quality of service in edge cloud architectures

Example methods, apparatus, and systems to manage quality of service with respect to service level agreements in a computing device are disclosed. An example apparatus includes a first mesh proxy assigned to a first platform-agnostic application, the first mesh proxy to generate a first resource request signal based on a first service level agreement requirement from the first platform-agnostic application; a second mesh proxy assigned to a second platform-agnostic application, the second mesh proxy to generate a second resource request signal based on a second service level agreement requirement from second platform-agnostic application; and a load balancer to allocate hardware resources for the first platform-agnostic application and the second platform-agnostic application based on the first resource request signal and the second resource request signal.

Methods and apparatus to manage quality of service with respect to service level agreements in a computing device

Technologies for securing a virtualization network function (VNF) image includes a security server to generate a wrapping cryptographic key to wrap a private key of the VNF image and replace the private key with the wrapped private key to secure the private key. During operation, the VNF image may be authenticated by a network function virtualization (NFV) server as needed. Additionally, the signature of the VNF image may be updated each time the VNF image is shutdown to ensure the continued authenticity of the VNF image.

Technologies for securing network function virtualization images

Technologies for analyzing and optimizing workloads (e.g., virtual network functions) executing on edge resources are disclosed. According to one embodiment disclosed herein, a compute device launches a virtualized system including a virtual network function and a performance manager, the performance manager to monitor a current resource usage of the virtual network function as a function of a performance profile. The compute device determines, in response to a determination that one or more quality-of-service (QoS) requirements is not satisfied, whether one or more resources from the platform are available for satisfying the QoS requirements. The compute device receives, in response to a determination that the one or more resources are available for satisfying the QoS requirements, the one or more resources and updates the performance profile as a function of the received resources.

Technologies for autonomous edge compute instance optimization and auto-healing using local hardware platform QoS services

Technologies for providing multi-tenant support in edge resources using edge channels include a device that includes circuitry to obtain a message associated with a service provided at the edge of a network. Additionally, the circuitry is to identify an edge channel based on metadata associated with the message. The edge channel has a predefined amount of resource capacity allocated to the edge channel to process the message. Further, the circuitry is to determine the predefined amount of resource capacity allocated to the edge channel and process the message using the allocated resource capacity for the identified edge channel.

Technologies for providing multi-tenant support using one or more edge channels

Technologies for load balancing on a network device in an edge network are disclosed. According to one embodiment, a network device receives, in the edge network, a request to access a function. The request includes one or more performance requirements. The network device identifies, as a function of an evaluation of the performance requirements and on monitored properties of each device associated with the network device, one or more of the devices to service the request. The network device selects one of the identified devices according to a load balancing policy and sends the request to the selected device.

Technologies for network device load balancers for accelerated functions as a service

A device of a service coordinating entity includes communications circuitry to communicate with a plurality of access networks via a corresponding plurality of network function virtualization (NFV) instances, processing circuitry, and a memory device. The processing circuitry is to perform operations to monitor stored performance metrics for the plurality of NFV instances. Each of the NFV instances is instantiated by a corresponding scheduler of a plurality of schedulers on a virtualization infrastructure of the service coordinating entity. A plurality of stored threshold metrics is retrieved, indicating a desired level for each of the plurality of performance metrics. A threshold condition is detected for at least one of the performance metrics for an NFV instance of the plurality of NFV instances, based on the retrieved plurality of threshold metrics. A hardware resource used by the NFV instance to communicate with an access network is adjusted based on the detected threshold condition.

Technologies for dynamically allocating acceleration units of a network device include a network device configured to determine a present compute usage value associated with a workload of the virtual machine, determine whether to accelerate the virtual machine as a function of the present compute usage and a compute capability usage limit, and select, in response to a determination to accelerate the virtual machine, an acceleration unit from one or more acceleration units, as a function of a type of the workload. Additionally, the network device is configured to allocate the identified acceleration unit. Other embodiments are described and claimed.

Technologies for dynamically allocating hardware acceleration units to process data packets

Technologies for secure inter-virtual-machine shared memory communication include a computing device with hardware virtualization support. A virtual machine monitor (VMM) authenticates a view switch component of a target virtual machine. The VMM adds configures a secure memory view to access a shared memory segment. The shared memory segment may include memory pages of a source virtual machine or the VMM. The view switch component switches to the secure memory view without generating a virtual machine exit event, using the hardware virtualization support. The view switch component may switch to the secure memory view by modifying an extended page table (EPT) pointer. The target virtual machine accesses the shared memory segment via the secure memory view. The target virtual machine and the source virtual machine may coordinate ownership of memory pages using a secure view control structure stored in the shared memory segment. Other embodiments are described and claimed.

Technologies for secure inter-virtual-machine shared memory communication

Growing community of inventors

Tempe, AZ, United States of America

Rashmin N Patel