In this paper, we propose an extended version of UMR, called UMR2, that overcomes these limitations and adopts a worker selection policy that aims at minimizing the makespan. We, theoretically and experimentally, show that UMR2 is superior to UMR, specifically in a WAN computing platform such as the Cloud environments. | JOURNAL OF SCIENCE OF HNUE Natural Sci. 2011 Vol. 56 No. 7 pp. 44-57 RESOURCES MANAGEMENT ALGORITHM FOR THE CLOUD ENVIRONMENT Phan Thanh Toan Nguyen The Loc Hanoi University of Education E-mail locnt@ Abstract. Numerous studies have been targeting the problem of scheduling divisible workloads in Cloud computing environments. The UMR Uniform Multi-Round algorithm stands out from all others by being the first close- form optimal scheduling algorithm. However present algorithms including the UMR do not pay due attention to optimizing the set of workers that get selected to participate in processing workload chunks. In addition to the absence of a good resource selection policy the UMR relies primarily in its computation on the CPU speed and overlooks the role of other key parameters such as network bandwidth. In this paper we propose an ex- tended version of UMR called UMR2 that overcomes these limitations and adopts a worker selection policy that aims at minimizing the makespan. We theoretically and experimentally show that UMR2 is superior to UMR specifically in a WAN computing platform such as the Cloud environments. Keywords Divisible loads multi-round algorithms cloud computing. 1. Introduction By definition a divisible load is a load that can be partitioned into any arbi- trary number of load fractions 1 . This kind of workload arises in many domains of science such as protein sequence analysis simulation of cellular micro physiology and more 2 3 . Per the divisible load theory 1 the scheduling problem is identified as Given an arbitrary divisible workload in what proportion should the workload be partitioned and distributed among the workers so that the entire workload is processed in the shortest possible time. Any scheduling algorithm should address the following issues Workload partitioning problem This problem is concerned with the method by which the algorithm should divide the workload in order to dispatch to workers. Resource selection .
