Coordinated Resources Allocation Heuristics in Distributed Computing

In this work, we propose and study heuristics for parallel jobs execution and efficient resources co-allocation in heterogeneous computing environments. Existing modern job- flow execution features and realities impose many restrictions for the resources allocation procedures and applicable scheduling criteria. Subject to these restrictions a special dynamic programming scheme is proposed to select resources depending on their meta-features as secondary scheduling criteria. Such secondary optimization criteria are commonly referred as breaking a tie rules. Thus, while maintaining the same primary scheduling criterion outcomes it is sometimes possible to affect global resources utilization efficiency by choosing the appropriate secondary criteria. Basing on a conservative backfilling algorithm we study different breaking a tie heuristic strategies and their affect on the integral job-flow execution characteristics.