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Resource-Efficient Pareto-Optimal Green Scheduler Architecture

Author

Listed:
  • Urmila Shrawankar

    (G. H. Raisoni College of Engineering, Nagpur, India)

  • Chetan Ashokrao Dhule

    (G. H. Raisoni College of Engineering, Nagpur, India)

Abstract

Rapidly developing cloud technology with enormous number of clients creates need of reducing power consumption of data centers. VM live migration is the most promising tool to achieve resource consolidation but it creates overheads in terms of additional CPU, disk I/O and network bandwidth utilization. This paper proposes a power-aware VM live migration based dynamic VM consolidation mechanism that focuses on reduction in datacenter’s resource utilization. Proposed mechanism is Pareto Optimal because during live migration it not only optimize the migration overheads but also select the VM and destination server by considering all the performance overheads to be generated during and after live migration. The proposed algorithm reduces nearly 60% of the VMs migration overheads. In terms of energy saving the proposed mechanism is 43% more efficient than the greedy scheduling approach and about 47% more energy efficient than the round-robin approach and thus achieves green computing goal.

Suggested Citation

  • Urmila Shrawankar & Chetan Ashokrao Dhule, 2022. "Resource-Efficient Pareto-Optimal Green Scheduler Architecture," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 12(2), pages 1-14, April.
    • Handle: RePEc:igg:jcac00:v:12:y:2022:i:2:p:1-14
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCAC.305855
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    Cited by:

    1. Zhou, Yufei & Wang, Sihan & Zhang, Nuo, 2023. "Dynamic decision-making analysis of Netflix's decision to not provide ad-supported subscriptions," Technological Forecasting and Social Change, Elsevier, vol. 187(C).

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