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Reliability-Based Resource Scheduling Approach Using Hybrid PSO-GA in Mobile Computational Grid

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 94))

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Abstract

The inclusion of smartphone/mobile nodes as a part of grid computing increases the computation limits of the static grid while at the same time adds to the complexity owing to the associated factors like mobility, limited power, and weak wireless connectivity. This work presents a hybrid PSO-GA (Particle Swarm Optimization––Genetic Algorithm) based resource allocation strategy for reliable execution of jobs within a reasonable time for the computational mobile grid. Before allocating the task to the resources, the best nodes as per the fitness function are selected under the given constraints in order to meet the scheduling objectives. PSO-GA is a hybrid approach, proving to be more efficient and effective than single PSO or GA. Simulation study supports the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Krishan Veer Singh & Zahid Raza

Authors
  1. Krishan Veer Singh
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  2. Zahid Raza
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Corresponding author

Correspondence to Krishan Veer Singh .

Editor information

Editors and Affiliations

  1. Smart Grid and Renewable Energy, University of Agder, Kristiansand, Norway

    Mohan L. Kolhe

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, NIT Agartala, Tripura, India

    Munesh C. Trivedi

  4. Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India

    Krishn K. Mishra

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Singh, K.V., Raza, Z. (2020). Reliability-Based Resource Scheduling Approach Using Hybrid PSO-GA in Mobile Computational Grid. In: Kolhe, M., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 94. Springer, Singapore. https://doi.org/10.1007/978-981-15-0694-9_11

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  • DOI: https://doi.org/10.1007/978-981-15-0694-9_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0693-2

  • Online ISBN: 978-981-15-0694-9

  • eBook Packages: EngineeringEngineering (R0)

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