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Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014 pp 43–52Cite as

Hybrid Job Scheduling Algorithm for Cloud Computing Environment

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 303))

Abstract

In this paper with the aid of genetic algorithm and fuzzy theory, we present a hybrid job scheduling approach, which considers the load balancing of the system and reduces total execution time and execution cost. We try to modify the standard Genetic algorithm and to reduce the iteration of creating population with the aid of fuzzy theory. The main goal of this research is to assign the jobs to the resources with considering the VM MIPS and length of jobs. The new algorithm assigns the jobs to the resources with considering the job length and resources capacities. We evaluate the performance of our approach with some famous cloud scheduling models. The results of the experiments show the efficiency of the proposed approach in term of execution time, execution cost and average Degree of Imbalance (DI).

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Islamic Azad University, Dezful Branch, Dezful, Iran

    Saeed Javanmardi

  2. Department of Information Engineering Electronics and Telecommunications (DIET), University Sapienza of Rome, Rome, Italy

    Mohammad Shojafar, Danilo Amendola & Nicola Cordeschi

  3. School of Information, Dalian Maritime University, 116026, Dalian, China

    Hongbo Liu

  4. IT4Innovations, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Ajith Abraham

  5. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation, and Research Excellence, Auburn, USA

    Ajith Abraham

Authors
  1. Saeed Javanmardi
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  2. Mohammad Shojafar
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  3. Danilo Amendola
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  4. Nicola Cordeschi
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  5. Hongbo Liu
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  6. Ajith Abraham
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Corresponding author

Correspondence to Saeed Javanmardi .

Editor information

Editors and Affiliations

  1. Department of Computer Science Faculty of Elec. Eng. and Comp. Sci., VŠB-TUO, Ostrava-Poruba, Czech Republic

    Pavel Kömer

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Washington, Alabama, USA

    Ajith Abraham

  3. Department of Computer Science Faculty of Elect. Eng. and Comp. Sci., VŠB-TUO, Ostrava-Poruba, Czech Republic

    Václav Snášel

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© 2014 Springer International Publishing Switzerland

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Javanmardi, S., Shojafar, M., Amendola, D., Cordeschi, N., Liu, H., Abraham, A. (2014). Hybrid Job Scheduling Algorithm for Cloud Computing Environment. In: Kömer, P., Abraham, A., Snášel, V. (eds) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Advances in Intelligent Systems and Computing, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-319-08156-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-08156-4_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08155-7

  • Online ISBN: 978-3-319-08156-4

  • eBook Packages: EngineeringEngineering (R0)

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