Title: Self-organised resource assignment for on-demand services in the cloud platform

Authors: Zhiqiang Ruan; Dan Yang

Addresses: College of Computer and Control Engineering, Minjiang University, Fuzhou, China; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, Liaoning, China ' College of Computer and Control Engineering, Minjiang University, Fuzhou, China; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, Liaoning, China

Abstract: It is more popular for a multimedia service provider (MCSP) to deploy many data centres (DCs) in different geographic locations over cloud for delivering video-on-demand (VoD) services to a lot of users. One primary task of the MCSP is to maximise its profit while guarantee the user's quality-of-service (QoS) requirements. However, the stochastic arrival of user requests and the capacity restriction of individual DC make resource management in distributed cloud more challenging than in a general cloud. We present a resource assignment strategy that can accommodate heterogeneous network resources and QoS demands by converting the request distribution problem into the constrained function optimisation problem. An online algorithm is developed and certified approximating to the optimum solution. Compared with other alternatives, our algorithm can cut down more than 35% of operational cost without degrading the QoS of end users.

Keywords: self-organised; resource assignment; cloud platform.

DOI: 10.1504/IJCSE.2020.107248

International Journal of Computational Science and Engineering, 2020 Vol.22 No.1, pp.62 - 73

Received: 22 Feb 2019
Accepted: 14 May 2019
Published online: 11 May 2020 *

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