Efficient dynamical system resource management method in cloud computing. Issue 23 (31st October 2019)

• Record Type: Journal Article
• Authors: Wu, Tianshu; Wang, Shuai; Shi, Xiaoyu
• Is Part Of: Journal of engineering. Volume 2019:Issue 23(2019)
• Page Start: 8891
• Page End: 8894
• Publication Date: 2019-10-31
• Subjects: resource allocation -- virtualisation -- cloud computing -- linear quadratic control -- optimisation -- virtual machines; dynamical optimisation problem -- dynamical workloads -- robust workloads -- constrained boundary linear quadratic control method -- optimal resource allocation scheme -- system input -- system noise -- authors -- efficient dynamical system resource management method -- cloud computing -- virtualisation system -- efficient manage system resource -- optimal load -- different virtual machines -- single physical server -- dynamical web workloads -- system resource management problem; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2018.9138
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : The resource management of virtualisation system is a core issue in the field of cloud computing. For achieving the goal of efficient manage system resource without performance loss in clouding environment, the authors propose an optimal load balancing controller to assign the resource to different virtual machines, which run on a single physical server. Here, the authors focus on dynamical web workloads that the system resource management problem can be formulated as a dynamical optimisation problem. In the face of dynamical and robust workloads, the authors present an alternative approach based on the constrained boundary linear quadratic control (cBLQC) method, the optimal resource allocation scheme is solved by minimising the quadratic cost function with constrains on the system input and output. Different with existing works that assume a particular distribution for system noise or ignore the noise directly, the authors loosen the restrictions on system noise, which simply assume that system noise belongs with some reasonable norm‐bounded set. Experiments on the Xen‐based platform with a set of workload patterns show that the efficiency of authors' method in terms of control precision and stability.