Abstract

The development of a huge amount of client’s job for equivalent performance on open-resource grid system is the main reason of system failures or delayed process due to grimy hardware, software vulnerability, as well as shared confined policy. In this study we represent highly reliability conditions in grid work scheduling and present a new procedure for scheduling by hybridization of intelligent water drop algorithm and particle swarm optimization technique and compare it with earliest deadline in the basis of first come first served. The IWDPSO algorithm is tested with two datasets namely Numerical Aerodynamic Simulation (NAS) and Parameter Sweep Application (PSA) and the results are tested with performance metrics makespan, slowdown and failure rate and grid utilization. The proposed algorithms results in effective usage of grid computing resources with reduced makespan, slowdown and failure rate. The proposed algorithm is compared with Risky-MinMin (RMM), Preemptive-MinMin (PMM) and Delay Tolerant Space-Time Genetic Algorithm (DTSTGA).

Keywords:

Grid , IWD , IWDPSO , job scheduling , NAS , PSA , PSO,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.