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A Combinatorial Multi-objective Particle Swarm Optimization Based Algorithm for Task Allocation in Distributed Computing Systems

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Advances in Computing and Communications (ACC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 193))

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Abstract

In a distributed computing system (DCS), the scheduling of tasks comprise of two phases, task allocation and task scheduling. The allocation of tasks to different processors is required to maximize the processors synergism in order to achieve the various objectives, such as, system throughput, reliability maximization and cost minimization. The task allocation also need to satisfy a set of system constraints related to memory and link capacity. This problem has been shown as NP-Hard. Most of meta-heuristic algorithms deal with the task allocation problem as single objective or transform the multiple objectives into single objective. This paper presents a combinatorial multi-objective particle swarm optimization based (CMOPSO) algorithm to deal with the multiple conflicting objectives of task allocation problem simultaneously without transforming them to single objective. The performance of the algorithm is compared with a NSGA-II based task allocation algorithm; results manifest that the algorithm shows good performance under different problem scales and task interaction density.

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Author information

Authors and Affiliations

  1. Department of Computer Science Engineering, KIIT University, Bhubaneswar, Odisha, India

    Rahul Roy & Madhabananda Das

  2. Department of Information and Communication Technology, Fakir Mohan University, Balasore, 756019, Odisha, India

    Satchidananda Dehuri

Authors
  1. Rahul Roy
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  2. Madhabananda Das
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  3. Satchidananda Dehuri
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Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs (MIR Labs), Auburn, 98071-2259, Washington, USA

    Ajith Abraham

  2. Departamento de Comunicaciones, Universidad Politcnica de Valencia, 46071, Valencia, Spain

    Jaime Lloret Mauri

  3. Avaya Labs Research, Basking Ridge, NJ, USA

    John F. Buford

  4. University of Massachusetts, 100 Morrissey Blvd., 02125-3393, Boston, MA, USA

    Junichi Suzuki

  5. Rajagiri School of Engineering and Technology, Rajagiri Valley Kakkanad, 682 039, Kochi, India

    Sabu M. Thampi

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© 2011 Springer-Verlag Berlin Heidelberg

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Roy, R., Das, M., Dehuri, S. (2011). A Combinatorial Multi-objective Particle Swarm Optimization Based Algorithm for Task Allocation in Distributed Computing Systems. In: Abraham, A., Mauri, J.L., Buford, J.F., Suzuki, J., Thampi, S.M. (eds) Advances in Computing and Communications. ACC 2011. Communications in Computer and Information Science, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22726-4_13

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  • DOI: https://doi.org/10.1007/978-3-642-22726-4_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22725-7

  • Online ISBN: 978-3-642-22726-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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