First EAI International Conference on Computer Science and Engineering

Research Article

Experimental Performance Analysis of Job Scheduling Algorithms on Computational Grid using Real Workload Traces

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  • @INPROCEEDINGS{10.4108/eai.27-2-2017.152264,
        author={Syed Nasir Mehmood Shah and Ahmad Kamil Mahmood and Saddaf Rubab and Mohd Fadzil Hassan},
        title={Experimental Performance Analysis of Job Scheduling Algorithms on Computational Grid using Real Workload Traces},
        proceedings={First EAI International Conference on Computer Science and Engineering},
        publisher={EAI},
        proceedings_a={COMPSE},
        year={2017},
        month={2},
        keywords={Distributed systems Cluster Grid computing Grid scheduling Workload modeling Performance evaluation Simulation Load balancing Task synchronization Parallel processing},
        doi={10.4108/eai.27-2-2017.152264}
    }
    
  • Syed Nasir Mehmood Shah
    Ahmad Kamil Mahmood
    Saddaf Rubab
    Mohd Fadzil Hassan
    Year: 2017
    Experimental Performance Analysis of Job Scheduling Algorithms on Computational Grid using Real Workload Traces
    COMPSE
    EAI
    DOI: 10.4108/eai.27-2-2017.152264
Syed Nasir Mehmood Shah1,*, Ahmad Kamil Mahmood, Saddaf Rubab, Mohd Fadzil Hassan
  • 1: Department of Computer Sciences, Dr. A. Q. Khan Institute of Computer Sciences & Information Technology, Kahuta, Pakistan
*Contact email: dr.shah@kicsit.edu.pk

Abstract

Grid, an infrastructure for resource sharing, currently has shown its importance in many scientific applications requiring tremendously high computational power. Grid computing, whose resources are distributed, heterogeneous and dynamic in nature, introduces a number of fascinating issues in job scheduling. Grid scheduler is the core component of a grid and is responsible for efficient and effective utilization of heterogeneous and distributed resources. This paper presents comparative performance analysis of our proposed job scheduling algorithm with other well known job scheduling algorithms considering the quality of service parameters. The main thrust of this work was to conduct a quality of service based experimental performance evaluation of job scheduling algorithms on computational Grid in true dynamic environment. Experimental evaluation confirmed that proposed scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability. This paper includes statistical analysis of real workload traces to present the nature and behavior of jobs.