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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: (1) how to find global optimized solutions efficiently; (2) 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 Δt. Compared with state-of-the-art ABC based policies, the experimental results show that the proposed algorithm efficiently reduces energy consumption and SLA violation

FP-ABC: Fast and Parallel ABC Based Energy-Efficiency Live VM Allocation Policy in Data Centers