Walter Hinton - Westminster CO, US Garry Anderson - Westminster CO, US Richard Rector - Erie CO, US Bienvenido Reyes - Longmont CO, US Gary Ritzer - Lafayette CO, US Arthur Scrimo - Northglenn CO, US Eric West - Lakewood CO, US
International Classification:
G06F003/00
US Classification:
710/001000
Abstract:
A method and system for characterizing data storage usage by a host in a data storage system that provides a host-specific access area in a storage device. Access is gained to the access area and blocks of data from the access area are retrieved and stored in buffers. The stored data is classified as allocated as an organized data structured defined by a particular file system or non-typical system. The classifying includes sequentially mapping the data into file system data structures until a match is obtained and then the mapped data structure is stored. The match is verified by retrieving expected values for a file system and comparing the mapped values with the expected values. The mapped data is used to determine host storage information, such as number of blocks, number of the used data blocks, free space, number of files, location of files, and size of files.
Systems, Methods, Computing Platforms, And Storage Media For Administering A Distributed Edge Computing System Utilizing An Adaptive Edge Engine
- Boulder CO, US Kurt Rinehart - Boulder CO, US Matthew Wickman - Arvada CO, US Gary Ritzer - Longmont CO, US Lucas Caballero - Broomfield CO, US Glenn Slaven - Berridale, NSW, AU Jason Stangroome - Wamberal, NSW, AU Pavel Nikolov - Homebush West, NSW, AU Ivan Hamilton - Cumberland Reach, NSW, AU Calvin John Brewer - Centennial CO, US
International Classification:
H04L 47/125 H04L 47/22 H04L 47/2416 H04L 47/10
Abstract:
Systems, methods, computing platforms, and storage media for administering a distributed edge computing system utilizing an adaptive edge engine based on a finite state machine behavioral model are disclosed. Exemplary implementations may: select a first workload from one or more workloads; access, for the selected workload, one or more location optimization strategies from a plurality of location optimization strategies; and optimize an objective function across a portion of the one or more endpoints; select one or more endpoints; deploy the workload on at least one selected endpoint; monitor the health of the endpoint-workload deployment; and direct network traffic to the appropriate endpoint.
Systems, Methods, Computing Platforms, And Storage Media For Administering A Distributed Edge Computing System Utilizing An Adaptive Edge Engine
- Boulder CO, US Kurt Rinehart - Boulder CO, US Matthew Wickman - Arvada CO, US Gary Ritzer - Longmont CO, US Lucas Caballero - Broomfield CO, US Glenn Slaven - Berridale, AU Jason Stangroome - Wamberal, AU Pavel Nikolov - Homebush West, AU Ivan Hamilton - Cumberland Reach, AU Calvin John Brewer - Centennial CO, US
International Classification:
H04L 12/803 H04L 12/853 H04L 12/801 H04L 12/815
Abstract:
Systems, methods, computing platforms, and storage media for administering a distributed edge computing system utilizing an adaptive edge engine based on a finite state machine behavioral model are disclosed. Exemplary implementations may: select a first workload from one or more workloads; access, for the selected workload, one or more location optimization strategies from a plurality of location optimization strategies; and optimize an objective function across a portion of the one or more endpoints; select one or more endpoints; deploy the workload on at least one selected endpoint; monitor the health of the endpoint-workload deployment; and direct network traffic to the appropriate endpoint.