US 12,079,660 B2
Evolutionary modelling based non-disruptive scheduling and management of computation jobs
Rohit Bahl, Kanata (CA); Stephen Williams, Stittsville (CA); and Debashish Ghosh, Ottawa (CA)
Assigned to Cisco Technology, Inc., San Jose, CA (US)
Filed by Cisco Technology, Inc., San Jose, CA (US)
Filed on Aug. 2, 2023, as Appl. No. 18/229,615.
Application 18/229,615 is a continuation of application No. 17/105,422, filed on Nov. 25, 2020, granted, now 11,734,062.
Application 17/105,422 is a continuation of application No. 16/161,666, filed on Oct. 16, 2018, granted, now 10,877,799, issued on Dec. 29, 2020.
Prior Publication US 2024/0045715 A1, Feb. 8, 2024
Int. Cl. G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06N 3/086 (2023.01); G06N 3/126 (2023.01); G06N 3/12 (2023.01)
CPC G06F 9/4881 (2013.01) [G06F 9/5038 (2013.01); G06N 3/126 (2013.01); G06F 9/4887 (2013.01); G06N 3/086 (2013.01); G06N 3/12 (2013.01)] 20 Claims
OG exemplary drawing
 
13. A method, comprising:
determining, based on a previous schedule of computing jobs, execution frequencies of the computing jobs;
generating a schedule of the computing jobs by:
selecting, for a first slot in the schedule, a first computing job having a highest execution frequency among the computing jobs; and
selecting, for a second slot in the schedule, a second computing job having a highest priority among the computing jobs with respect to an other characteristic of the computing jobs; and
cause at least one computing resource to execute the computing jobs based on the schedule.