US 12,260,262 B2
Dynamic data driven orchestration of workloads
Clyde Tanner Foster, II, Raleigh, NC (US); John F Gbruoski, Raleigh, NC (US); Mehrdad Ashrafian, Chapel Hill, NC (US); Karl David McCormick, II, Raleigh, NC (US); Joseph Kozhaya, Morrisville, NC (US); and John Henry Welborn, Jr., Cary, NC (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Aug. 11, 2020, as Appl. No. 16/990,249.
Prior Publication US 2022/0050728 A1, Feb. 17, 2022
Int. Cl. G06F 9/46 (2006.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06F 18/214 (2023.01)
CPC G06F 9/5083 (2013.01) [G06F 9/4881 (2013.01); G06F 9/505 (2013.01); G06F 18/214 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for dynamic workload orchestration based on data complexity, the method comprising:
receiving a workload for orchestration;
analyzing the workload;
generating a policy for complexity score computation based on information associated with the workload;
organizing the workload into respective portions of the workload;
computing complexity scores for the respective portions of the workload dynamically, wherein the complexity scores are computed at least in part based on parameters describing data associated with the respective portions of the workload, and wherein the complexity scores are computed at least in part based on the policy;
assigning the respective portions of the workload to compute resources based on respective complexity scores of the respective portions of the workload; and
executing load balancing and orchestration within the corresponding compute resources.