A Discrete Firefly Algorithm for Scheduling Jobs on Computational Grid

  • Adil Yousif
  • Sulaiman Mohd Nor
  • Abdul Hanan Abdullah
  • Mohammed Bakri Bashir
Part of the Studies in Computational Intelligence book series (SCI, volume 516)


Computational grid emerged as a large scale distributed system to offer dynamic coordinated resources sharing and high performance computing. Due to the heterogeneity of grid resources scheduling jobs on computational grids is identified as NP-hard problem. This chapter introduces a job scheduling mechanism based on Discrete Firefly Algorithm (DFA) to map the grid jobs to available resources in order to finish the submitted jobs within a minimum makespan time. The proposed scheduling mechanism uses population based candidate solutions rather than single path solution as in traditional scheduling mechanism such as tabu search and hill climbing, which help avoids trapping in local optimum. We used simulation and real workload traces to evaluate the proposed scheduling mechanism. The simulation results of the proposed DFA scheduling mechanism are compared with Genetic Algorithm and Tabu Search scheduling mechanisms. The obtained results demonstrated that, the proposed DFA can avoid trapping in local optimal solutions and it could be efficiently utilized for scheduling jobs on computational grids. Furthermore, the results have shown that DFA outperforms the other scheduling mechanisms in the case of typical and heavy loads.


Computational grid Discrete optimization Firefly algorithm  Job scheduling 



This research is supported by the Ministry of Higher Education Malaysia (MOHE) and collaboration with Research Management Center (RMC) Universiti Teknologi Malaysia. This paper is financially supported by GUP GRANT (No. Vot: Q.J130000.7128.00H55).


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Adil Yousif
    • 1
  • Sulaiman Mohd Nor
    • 2
  • Abdul Hanan Abdullah
    • 1
  • Mohammed Bakri Bashir
    • 1
  1. 1.Faculty of ComputingUniversiti Teknologi MalaysiaSkudaiMalaysia
  2. 2.Faculty of Electrical EngineeringUniversiti Teknologi MalaysiaSkudaiMalaysia

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