Cooperative Scheduling of Bag-of-Tasks Workflows on Hybrid Clouds

We address the problem of scheduling a class of large-scale applications inspired from real-world on hybrid Clouds, characterized by a large number of homogeneous and concurrent tasks that are the main sources of bottlenecks but open great potential for optimization. We formulate the scheduling problem as a new sequential cooperative game and propose a communication- and storage-aware multi-objective algorithm that optimizes two user objectives (execution time and economic cost) while fulfilling two constraints (network bandwidth and storage requirements). We present comprehensive experiments using both simulation and real-world applications that demonstrate the efficiency and effectiveness of our approach in terms of algorithm complexity, make span, cost, system-level efficiency, fairness, and other aspects compared with other related algorithms.