Energy Minimization for Cloud Services with Stochastic Requests.

Energy optimization for cloud computing services has gained a considerable momentum over the recent years. Unfortunately, minimizing energy consumption of cloud services has its own unique research problems and challenges. More specifically, it is difficult to select suitable servers for cloud service systems to minimize energy consumption due to the heterogeneity of servers in cloud centers. In this paper, the energy minimization problem is considered for cloud systems with stochastic service requests and system availability constraints where the stochastic cloud service requests are constrained by deadlines. An energy minimization algorithm is proposed to select the most suitable servers to achieve the energy efficiency of cloud services. Our intensive experimental studies based on both simulated and real cloud instances show the proposed algorithm is much more effective with acceptable CPU utilization, saving up to 61.95% energy consumption, than the existing algorithms.