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In this paper, the cloud services optimization problem considering energy consumption cost is discussed. The queue model is presented for customer request service on data center. Since the server energy utility is based on the CPU core frequency, the novel trade-off optimization model between services revenue and energy loss cost is proposed in the paper, including allocating the dynamic CPU frequency...
In order to overcome the disadvantages of premature and local convergence in the traditional particle swarm optimization (PSO), an improved chaotic PSO algorithm based on adaptive inertia weight (AIWCPSO) is proposed. The initial population is generated by using chaotic mapping appropriately, in order to improve both the diversity of population and the periodicity of particles. The value of the new...
Particle swarm optimization is introduced to solve the problem in this paper. Instead of solving a group of non-linear equations, forward kinematics is solved by computing the extremum of a function. And accurate solutions can be obtained by the global and local searching abilities of advanced particle swarm optimization. It overcomes the shortage that precision is greatly influenced by initial values...
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