Title: Adaptive resource management for spot workers in cloud computing environment

Authors: Lung-Pin Chen; Fang-Yie Leu; Hsin-Ta Chiao; Hung-Jr Shiu

Addresses: Computer Science Department, Tunghai University, Taiwan ' Computer Science Department, Tunghai University, Taiwan; Emergency Response Management Center, Ming-Chun University, Taiwan ' Computer Science Department, Tunghai University, Taiwan ' Computer Science Department, Tunghai University, Taiwan

Abstract: Due to flexible scheduling requirements of various service applications, a cloud platform usually has some temporarily unleased machines. To make cost-effective of the platform, such a considerable number of idle workers can be collected to perform malleable tasks. However, these workers are considered unstable since they can be interrupted unexpectedly by the resource broker. This paper proposes a resource management approach that employs replication to increase resource availability. We will show that increasing the replication factor can improve the worker reliability, but on the contrary, it also worsens the overhead of computational redundancy. An algorithm that can effectively control the replication factor so as to adapt to the changing workload and maintain the system performance is also developed.

Keywords: cloud computing; grid computing; resource allocation.

DOI: 10.1504/IJWGS.2022.126124

International Journal of Web and Grid Services, 2022 Vol.18 No.4, pp.437 - 452

Received: 13 Sep 2021
Received in revised form: 07 Jan 2022
Accepted: 03 Apr 2022
Published online: 11 Oct 2022 *

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