Virtual Instruments Corporation

Virtual Instruments Worldwide, Inc.

Francis Niestemski

Nicholas York

Ryan E Perkowski

Devin Blinn Avery

Leo Szumel

Xiongwei He

Dale Coldiron

Zhipeng Gong

A method comprising: receiving an analytic task which includes a priority indicator associated with the analytic task, determining a position of the analytic task in a task queue, the task queue arranged in an order according to their priority indicators, selecting the analytic task based on the order of the task queue, sending the analytic task to an analytics service to determine if the analytics service has sufficient available resources to perform the analytic task, receiving an indication that the analytics service does not have sufficient available resources to perform the analytic task, repositioning the analytic task within the task queue, selecting the analytic task from the task queue based on the order of the task queue and a new position of the analytic task, sending the analytic task to the analytics service, and retrieving another analytic task to send to the analytics service.

Methods and system for throttling analytics processing

A method comprising: receiving object identifiers associated with each entity of an enterprise network, receiving relationship data indicating directionality of data flow between two or more entities of enterprise network, receiving search query which includes at least one of an object identifier associated with one of the entities or relationship data indicating directionality of data flow associated with one of the entities, traversing a portion of topology to identify objects of the portion of the topology and a pivot point, the pivot point being directionally coupled to at least three objects, identifying two mini-topologies based on two of the least three objects of the pivot point, traversing each of the two mini-topologies to identify further objects within the portion of the topology, generating a partial topology based on the traversal of the portion of the topology and of the mini-topologies, and providing information including objects identified in the partial topology.

Systems and methods for hub and spoke cross topology traversal

An example method comprises receiving a begin time to initiate storage network traffic data collection from a plurality of data probes integrated within an enterprise network, collecting network data identifying HBA ports used to communicate with storage ports from the probes, analyzing the network data to determine attributes of network traffic, determining for each storage unit: a penalty score for each of the storage ports determining a reconfiguration of a storage unit or HBA based at least in part on the total penalty score, simulating changes of the reconfiguration of the storage unit or the HBA and simulate storage network traffic, applying the simulated storage network traffic on the simulated changes of the reconfiguration of the storage unit or HBA to determine improvements, and outputting instructions to enable reconfiguration of the storage unit or HBA.

Systems and methods of application-aware improvement of storage network traffic

A network monitor is used to determine resource (e.g., CPU, memory, storage, or network) utilization of one or more virtual machines on one or more corresponding servers. Using resource utilization data for an original configuration of the virtual machines on the servers, the described system and methods simulate reconfigurations of various VMs on servers, determines resource utilization of the simulated reconfigurations, and proposes a reconfiguration that results in lower resource utilization across the one or more corresponding servers.

Virtual machine processor and memory resource coordinator

A system for improving performance of a network includes a monitor that obtains data sets corresponding to network performance, infers characteristics from the data set and generates visualizations and recommendations. In one aspect, the network is a storage area network and the system generates a box plot showing response time based on inferred queue depth, and recommending a queue depth setting if possible.

Growing community of inventors

Longmeadow, MA, United States of America

Francis Niestemski