Author/Authors :
Jiang,Jianhua School of Management Science and Information Engineering - Jilin University of Finance and Economics, China , Feng,Yunzhao School of Management Science and Information Engineering - Jilin University of Finance and Economics, China , Parmar,Milan International Department - Faculty of Computer Science and Information Management - Hunan University of Arts and Science, Changde, China , Li, Keqin Department of Computer Science - State University of New York - New Paltz, USA
Abstract :
Virtual machine (VM) technology is one of the energy-efficiency approaches to save energy with acceptable quality of service (QoS). In our previous studies, Artificial Bee Colony (ABC) based VM allocation policy can make a good tradeoff between performance and energy consumption. However, there are two problems in state-of-the-art ABC based approaches: () how to find global optimized solutions efficiently; () how to minimize the decision time of VM allocation. To solve these two problems, the idea of simulated annealing is adopted to get a better global optimum, and the idea of gradient descent is applied to accelerate the speed of finding solution space in . Compared with state-of-the-art ABC based policies, the experimental results show that the proposed algorithm efficiently reduces energy consumption and SLA violation.
Keywords :
Virtual machine (VM) technology , FP-ABC , Data Centers , service (QoS) , ABC based policies
