Research Area:  Cloud Computing

Abstract:

Scheduling multiple large-scale parallel workflow applications on heterogeneous computing systems like hybrid clouds is a fundamental NP-complete problem that is critical to meeting various types of QoS (Quality of Service) requirements. This paper addresses the scheduling problem of large-scale applications inspired from real-world, characterized by a huge number of homogeneous and concurrent bags-of-tasks that are the main sources of bottlenecks but open great potential for optimization. The scheduling problem is formulated 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, makespan, cost, system-level efficiency, fairness, and other aspects compared with other related algorithms.

Keywords:  

Author(s) Name:  Rubing Duan; Radu Prodan; Xiaorong Li

Publisher name:  IEEE

DOI:  10.1109/TCC.2014.2303077

Volume Information:  Volume: 2, Issue: 1, Jan.-March 2014, Page(s): 29 - 42

Paper Link:   https://ieeexplore.ieee.org/abstract/document/6727390