%0 Conference Paper
%A Shah, S.N.M.
%A Mahmood, A.K.B.
%A Oxley, A.
%D 2010
%F scholars:975
%K Cluster; Distributed systems; Grid scheduling; Load balancing; Parallel processing; Performance evaluation; Robustness; Simulation; Task synchronization; Workload modeling, Cluster computing; Ecosystems; Grid computing; Parallel architectures; Program processors, Scheduling algorithms
%P 234-239
%R 10.1145/1936254.1936298
%T Analysis and evaluation of Grid scheduling algorithms using real workload traces
%U https://khub.utp.edu.my/scholars/975/
%X Computational grid has the potential for solving large-scale scientific problems using distributed resources. Grid scheduling is a vital component of a Computational Grid infrastructure. In this paper, we evaluate our proposed Grid scheduling algorithms (the Multilevel Hybrid Scheduling Algorithm and the Multilevel Dual Queue Scheduling Algorithm) using real workload traces, taken from leading computational centers. An extensive performance comparison is presented using real workload traces to evaluate the efficiency of scheduling algorithms. To facilitate the research, a software tool has been developed which produces a comprehensive simulation of a number of Grid scheduling algorithms. The tool's output is in the form of scheduling performance metrics. The experimental results, based on performance metrics, demonstrate that the performances of our Grid scheduling algorithms give good results. Our proposed scheduling algorithms also support true scalability, that is, they maintain an efficient approach when increasing the number of CPUs or nodes. This paper also includes a statistical analysis of workload traces to present the nature and behavior of jobs. Copyright © 2010 ACM.
%Z cited By 9; Conference of International Conference on Management of Emergent Digital EcoSystems, MEDES'10 ; Conference Date: 26 October 2010 Through 29 October 2010; Conference Code:84022