In this work, a job-flow scheduling approach for Grid virtual organizations (VOs) is proposed and studied. Users and resource providers preferences, VOs internal policies, resources geographical distribution along with local private utilization impose specific requirements for efficient scheduling according to different, usually contradictive, criteria. With increasing resources utilization level the available resources set and corresponding decision space are reduced. In order to improve overall scheduling efficiency, we propose an anticipation scheduling heuristic. It includes a target (anticipated) pattern solution definition and a special replication procedure for efficient and feasible resources allocation. A proposed anticipation algorithm is compared against conservative backfilling variations using such criteria as average jobs response time (start and finish times) as well as users and VO economic criteria (execution time and cost).
Toporkov, V., Toporkova, A., & Yemelyanov, D. (2017). Heuristic of anticipation for fair scheduling and resource allocation in grid VOs. Studies in Computational Intelligence, 737, 27–37. https://doi.org/10.1007/978-3-319-66379-1_3