Parallel plants collaborative growth algorithm for virtual machine migration. (1st January 2014)

• Record Type: Journal Article
• Authors: Wang, Fei; Chen, Anting; Laili, Yuanjun; Zhang, Lin; Wan, Peng; Zhao, Dongming; Tao, Fei
• Is Part Of: International journal of service and computing oriented manufacturing. Volume 1:Number 3(2014)
• Page Start: 211
• Page End: 236
• Publication Date: 2014-01-01
• Subjects: virtual machine -- migration -- plant growth simulation algorithm -- parallel intelligent algorithm -- cloud computing; Computer integrated manufacturing systems -- Periodicals; Manufacturing industries -- Information technology -- Periodicals; Manufacturing industries -- Computer networks -- Periodicals; Service-oriented architecture (Computer science) -- Periodicals; 670.285
• Languages: English
• ISSNs: 2045-175X

Abstract

With the development of cloud computing, more and more virtual computing resources are provided as dynamic services to achieve green and agile computing for different kinds of projects. Virtual machine migration, as one of the main technologies, has brought huge influences on the executive and collaborative efficiency of virtual machines. However, the existing research focuses primarily on management and scheduling of virtual machines. And several studies concerning virtual machine migration in service-oriented computing still have great limitations. Especially, with the expansion of the scale of collaborative computing tasks, the complexity, as well as the number of virtual machines increased significantly. When the pre-allocation of virtual machines becomes unsuitable due to some resource failures or long waiting queue, migration of virtual machine becomes imperative. Considering the influence of initial allocation, this paper proposes a new parallel plant collaborative growth algorithm (namely Parallel-PCGA) which combines efficient plant growth optimisation operator and ring topology-based parallelisation. It brings an effective balance in solution time and accuracy. Experimental results prove that Parallel-PCGA shows high performance in large-scale virtual machine migration in cloud computing.