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A QoS Aware Binary Salp Swarm Algorithm for Effective Task Scheduling in Cloud Computing

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1199))

Abstract

Day by day task scheduling becomes a more challenging issue as the user’s demand increases in cloud computing. It is a tedious task to deliver resources according to the user’s request with satisfying quality of service (QoS) requirement for both user and service provider. Many researchers have proved that meta-heuristic algorithms give better results for this problem. It inspired us to adopt a recently proposed Salp Swarm Algorithm to optimize request–resource mapping in cloud computing. This proposed QoS aware Binary Salp Swarm algorithm (QBSSA) has been inspired by the nature of salp during the searching and navigating for food in the sea. In this paper, QBSSA is simulated and compared with other most popular meta-heuristic algorithms, i.e., Ant Colony Optimization (ACO), and Grey Wolf Optimization (GWO). From the simulation results, it is proved that QBSSA outperforms others in terms of makespan and resource utilization, throughput, and average waiting time.

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Authors and Affiliations

  1. Banasthali Vidyapith, Newai, Rajasthan, India

    Richa Jain & Neelam Sharma

Authors
  1. Richa Jain
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  2. Neelam Sharma
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Corresponding authors

Correspondence to Richa Jain or Neelam Sharma .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, India

    Chhabi Rani Panigrahi

  2. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, India

    Bibudhendu Pati

  3. Department of Computer Science, University of California, Davis, CA, USA

    Prasant Mohapatra

  4. Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  5. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Jain, R., Sharma, N. (2021). A QoS Aware Binary Salp Swarm Algorithm for Effective Task Scheduling in Cloud Computing. In: Panigrahi, C.R., Pati, B., Mohapatra, P., Buyya, R., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1199. Springer, Singapore. https://doi.org/10.1007/978-981-15-6353-9_43

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  • DOI: https://doi.org/10.1007/978-981-15-6353-9_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6352-2

  • Online ISBN: 978-981-15-6353-9

  • eBook Packages: EngineeringEngineering (R0)

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