Cloud services optimization problem on energy utility resource allocation

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 of server. The HPSO algorithm is proposed for solving the mixed integer programming model. Then novel particle encoding substituting discrete variables and continuous variables efficiently improves solution quality. Finally, the dynamic penalty function method is discussed to convert the constraint optimization problem to non-constraint optimization problem.