Authors: Yonghua Xiong; Ya Chen; Keyuan Jiang; Yongbing Tang
Addresses: School of Automation, China University of Geosciences, Wuhan, China ' School of Information Science and Engineering, Central South University, Changsha, China ' Department of Computer Information Technology and Graphics, Purdue University Calumet, Hammond, USA ' Department of Computer Information Technology and Graphics, Purdue University Calumet, Hammond, USA
Abstract: Energy efficiency has become an increasingly prominent issue in cloud computing. Task consolidation is an effective way to maximise utilisation of cloud computing resources and reduce energy consumption. Presented in this paper is an improved energy-aware task consolidation algorithm to optimise the scheduling of tasks in cloud computing data centres. Our algorithm was developed based on the linear relationship between energy consumption and the CPU utilisation. Instead of consolidating tasks to a service node until its CPU utilisation reaches 100%, our algorithm uses an optimal point, where the CPU utilisation of a service node reaches 70%, and ensures that every task is preferentially assigned to service nodes that satisfy the 70% CPU utilisation. Our experiments demonstrate that our algorithm can significantly reduce the energy consumption of cloud computing data centres without performance degradation while maintaining good performance compared to the energy-conscious task consolidation (ECTC) approach.
Keywords: cloud computing; energy-aware; task consolidation; data centre.
International Journal of High Performance Computing and Networking, 2017 Vol.10 No.4/5, pp.352 - 358
Available online: 18 Aug 2017 *Full-text access for editors Access for subscribers Purchase this article Comment on this article