Patent ID: 11966775
Assignee: SAP SE
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A computer-implemented method comprising:
receiving a plurality of requests to execute jobs within a cloud computing environment;
adding the plurality of requests to a request queue;
processing the plurality of requests in the request queue by:
determining computing resources available to execute each job corresponding to the plurality of requests;
determining, for each job, whether the job is seasonal or non-seasonal based on attributes of the job identified by parsing metadata information relating to the job, wherein the metadata information includes at least one of a job tracker ID, frequency, job type, schedule time or resource usage metrics for the job, and wherein seasonal jobs have a higher frequency of execution over non-seasonal jobs;
retrieving historical computing resource consumption information for each seasonal job;
for each job corresponding to the plurality of requests in the request queue, using either a seasonal autoregressive integrated moving average ((S)ARIMA) predictor or an autoregressive integrated moving average (ARIMA) predictor based on a seasonality of the request to generate, using an ensemble model ((S)ARIMA model) combining an autoregressive moving average (ARMA) model and an ARIMA model, a resource prediction for each job corresponding to the plurality of requests in the request queue characterizing resources to be consumed when executing such job based on the corresponding determined computing resources and the corresponding retrieved historical information, wherein generating the resource prediction for each job comprises selecting the (S)ARIMA) predictor to apply the (S)ARIMA model to estimate the resources to be consumed for each job having a seasonal job type, and selecting the ARIMA predictor to apply the ARIMA model to estimate the resources to be consumed for each job having a non-seasonal job type;
generating a plurality of batches of jobs based on the generated resource predictions for the jobs and the available computing resources;
scheduling execution of the plurality of batches of jobs by the cloud computing environment; and
executing, by the cloud computing environment, the plurality of batches of jobs in accordance with the scheduled execution.