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A new whale optimizer for workflow scheduling in cloud computing environment

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Abstract

Cloud computing environments enable real time applications on virtualized resources that can be provisioned dynamically. It is one of the efficient platform service which permits to enable the various applications based on cloud infrastructure. Nowadays workflow systems become an easy and efficient task for the development of scientific applications. Efficient workflow scheduling algorithms are employed to improve the resource utilization by enhancing the cloud computing performance and to meet the users’ requirements. Many scheduling algorithms have been proposed but they are not optimal to incorporate benefits of cloud computing. In this paper a new framework are introduced as whale optimizer algorithm (WOA) which mimics the social behaviour of humpback whales and aims to maximize the work completion for meeting QoS constraints such as deadline and budget. This proposed method outperforms well when compared with other techniques and measured in terms of makespan, deadline and it is applicable for real time applications.

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Correspondence to Sounder Rajan Thennarasu.

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Thennarasu, S.R., Selvam, M. & Srihari, K. A new whale optimizer for workflow scheduling in cloud computing environment. J Ambient Intell Human Comput (2020) doi:10.1007/s12652-020-01678-9

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Keywords

  • Wireless  communication
  • Service and semantic computing
  • Autonomic computing
  • Whale optimizer
  • Makespan
  • Bubble-net search mechanism