In parallel computation, the scheduling and mapping tasks is considered the most critical problem which needs High Performance Computing (HPC) to solve it by breaking the problem into subtasks and working on those subtasks at the same time. The application sub tasks are assigned to underline machines and ordered for execution according to its proceeding to grantee efficient use of available resources such as minimize execution time and satisfy load balance between processors of the underline machine. The underline infrastructure may be homogeneous or heterogeneous. Homogeneous infrastructure could use the same machines power and performance. While heterogeneous infrastructure include machines differ in its performance, speed, and interconnection. According to work in this paper a new dynamic task scheduling algorithm for Heterogeneous called a Clustering Based HEFT with Duplication (CBHD) have been developed. The CBHD algorithm is considered an amalgamation between the most two important task scheduling in Heterogeneous machine, The Heterogeneous Earliest Finish Time (HEFT) and the Triplet Clustering algorithms. In the CBHD algorithm the duplication is required to improve the performance of algorithm. A comparative study among the developed CBHD, the HEFT, and the Triplet Cluster algorithms has been done. According to the comparative results, it is found that the developed CBHD algorithm satisfies better execution time than both HEFT algorithm and Triplet Cluster algorithm, and in the same time, it achieves the load balancing which considered one of the main performance factors in the dynamic environment. (C) 2012 Faculty of Computers and Information, Cairo University. Production and hosting by Elsevier B.V. All rights reserved.
