G06F2209/506

Wi-Fi Virtualization
20220058047 · 2022-02-24 ·

In one embodiment, a wireless network system includes a set of one or more wireless radios, and a set of software for the wireless network system that comprises a data structure representing the set of one or more wireless radios and a virtualization module that registers one or more virtualized data structures representing a virtual proxy of the set of one or more wireless radios.

Allocating operators of a streaming application to virtual machines based on monitored performance

Performance thresholds are defined for operators in a flow graph for a streaming application. A streams manager deploys the flow graph to one or more virtual machines (VMs). The performance of each portion of the flow graph on each VM is monitored. A VM is selected. When the performance of the portion of the flow graph in the selected VM does not satisfy the defined performance threshold(s), a determination is made regarding whether the portion of the flow graph is underperforming or overperforming. When the portion of the flow graph is underperforming, the portion of the flow graph is split into multiple portions that are implemented on multiple VMs. When the portion of the flow graph is overperforming, a determination is made of whether a neighbor VM is also overperforming. When a neighbor VM is also overperforming, the two VMs may be coalesced into a single VM.

Estimating device and estimating method

An estimation device is capable of estimating the number of CPU cores allocated to modules of an information processing device, which employs a micro-service architecture, and performance. A number-of-cores calculation unit calculates the total number of CPU cores necessary to process a temporary processing performance value output by a performance calculation unit. The performance calculation unit causes the number-of-cores calculation unit to calculate the number of necessary CPU cores while repeatedly adding a processing performance value increment to the temporary processing performance, and obtains an upper limit value of processing performance that is a maximum temporary processing performance value not exceeding a predetermined upper limit number of allocable CPU cores.

Co-allocating a reservation spanning different compute resources types
09785479 · 2017-10-10 · ·

A system and method of reserving resources in a compute environment are disclosed. The method embodiment comprises receiving a request for resources within a computer environment, determining at least one completion time associated with at least one resource type required by the request, and reserving resources within the computer environment based on the determine of at least the completion time. A scaled wall clock time on a per resource basis may also be used to determine what resources to reserve. The system may determine whether to perform a start time analysis or a completion time analysis or a hybrid analysis in the process of generating a co-allocation map between a first type of resource and a second type of resource in preparation for reserving resources according to the generated co-allocation map.

System and method of performing a pre-reservation analysis to yield an improved fit of workload with the compute environment
09778959 · 2017-10-03 · ·

A system and method are disclosed for receiving a request for resources in a compute environment to process workload, the request including a specification of a quality of fit. The system generates a substantial maximum potential quality of fit based on compute environment with an assumption of no competing workload to yield an analysis. The system evaluates a first resource allocation and a second resource allocation against the analysis to yield the first fit in a respective second fit. The system selects one of the first resource allocation and the second resource allocation based on a comparison of the first fit to the second fit as well as a cost associated with any delays.

METHOD FOR OPERATING A VIRTUAL NETWORK INFRASTRUCTURE
20170279735 · 2017-09-28 ·

A method for operating a virtual network infrastructure, wherein a corresponding physical infrastructure comprises one or more physical infrastructure resources, includes monitoring utilization levels of one or more resource units of the one or more physical infrastructure resources for virtual resources requesting the one or more resource units; calculating average absolute resource utilization values based on the utilization levels for each of the virtual resources; calculating a reference resource of score (RRAS) for each of the one or more resource units of the one or more physical infrastructure resources, wherein the RRAS indicates an impact of the utilization of a reference resource unit on utilization of other resource units on a physical infrastructure resource using the calculated average absolute resource utilization values; and assigning resources by a virtual infrastructure controller (VIC) and/or a VIC-agent on a resource, based on the RRAS for the virtual resources.

Acquisition and maintenance of compute capacity
11243819 · 2022-02-08 · ·

A system for providing low-latency computational capacity from a virtual compute fleet is provided. The system may be configured to maintain a plurality of virtual machine instances on one or more physical computing devices, wherein the plurality of virtual machine instances comprises a first pool comprising a first sub-pool of virtual machine instances and a second sub-pool of virtual machine instances, and a second pool comprising virtual machine instances used for executing one or more program codes thereon. The first sub-pool and/or the second sub-pool may be associated with one or more users of the system. The system may be further configured to process code execution requests and execute program codes on the virtual machine instances of the first or second sub-pool.

Systems and methods for distributed resource management

Methods, nontransitory computer readable media, and systems are disclosed for servicing a job queue. Each job has node resource requirements. Composite job memory and processor requirements is determined from these requirements. Nodes that satisfy these requirements are identified by obtaining, for each class of a plurality of node classes: an availability score, a number of processers, and a memory capability. A request for nodes of a class is made when a demand score for the class satisfies the class availability score. An acknowledgement and updated availability score is received upon request acceptance. A declination is received upon request rejection. The submitting and receiving is performing multiple times, if needed, until each class has been considered for a request or sufficient acknowledgements are received to satisfy the composite requirements of the jobs. Each node in the cluster draws jobs from the queue subject to the collective requirements of the drawn jobs.

AUTOMATED DEVICE SELECTION AND PROVISIONING FOR DISTRIBUTED COMPUTING WORKLOADS
20220035678 · 2022-02-03 · ·

In one embodiment, an apparatus comprises a communication interface to communicate over a network, and a processor. The processor is to: receive a workload provisioning request from a user, wherein the workload provisioning request comprises information associated with a workload, a network topology, and a plurality of potential hardware choices for deploying the workload over the network topology; receive hardware performance information for the plurality of potential hardware choices from one or more hardware providers; generate a task dependency graph associated with the workload; generate a device connectivity graph associated with the network topology; select, based on the task dependency graph and the device connectivity graph, one or more hardware choices from the plurality of potential hardware choices; and provision a plurality of resources for deploying the workload over the network topology, wherein the plurality of resources are provisioned based on the one or more hardware choices.

Cloud resource utilization management
11429454 · 2022-08-30 · ·

Data is received characterizing a plurality of virtual resources executing application code and deployed within a remote computing environment. The remote computing environment is providing a first configuration of computing resources for execution of the plurality of virtual resources. Resource consumption information associated with the plurality of virtual resources is monitored via an application programing interface of the remote computing environment. A second configuration of computing resources for the plurality of virtual resources is determined using a set of rules and the resource consumption information. A request is transmitted to the remote computing environment to provide the second configuration of computing resources for execution of the plurality of virtual resources. Related apparatus, systems, techniques and articles are also described.