Authors: Zhihui Lu; Jie Wu; Jie Bao; Patrick C.K. Hung
Addresses: School of Computer Science, Fudan University, Shanghai, 200433, China; IT Management Research Department, Yokohama Research Laboratory, Hitachi Ltd., Japan ' Engineering Research Center of Cyber Security Auditing and Monitoring, Ministry of Education, 200433, China ' School of Computer Science, Fudan University, Shanghai, 200433, China ' Faculty of Business and IT, University of Ontario Institute of Technology, Ontario, Canada
Abstract: Managing virtualised computing, network and storage resources at large-scale in both public and private cloud datacentres is a challenging task. As an open source cloud operating system, OpenStack needs to be enhanced for managing cloud datacentre resources. In order to improve OpenStack functions to support cloud datacentre resource management, we present OCReM: OpenStack-based cloud datacentre resource monitoring and management scheme. First, we designed a virtual machine group life-cycle management module. Then, we designed and developed a cloud resource monitoring module based on the Nagios monitoring software and Libvirt interface. We conducted an integrated experiment to verify the performance improvement of group-oriented auto scaling and elastic load balancing policy based on real-time resource monitoring data. After that, we implemented the OCReM-EC2 hybrid cloud monitoring and auto scaling model. Finally, we analysed the prospective research direction and propose our future work.
Keywords: OpenStack; cloud computing; cloud datacentres; cloud resource management; auto scaling; elastic load balancing; ELB; hybrid cloud; cloud resource monitoring; virtual machines; lifecycle management; LCM.
International Journal of High Performance Computing and Networking, 2016 Vol.9 No.1/2, pp.31 - 44
Available online: 11 Feb 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article