A Safe Virtual Machine Scheduling Strategy for Energy Conservation and Privacy Protection of Server Clusters in Cloud Data Centers

Abstract

With the increasing scale of cloud data centers (CDCs), the energy consumption of CDCs is sharply increasing. In this article, an efficient energy-saving strategy is proposed for CDCs. The greedy virtual machine (VM) deployment strategy is obtained by using the least number of servers, the heuristic VM migration strategy is obtained by using the improved double threshold algorithm, and the comprehensive VM scheduling strategy of severs is obtained by combining deployment and migration strategies. Furthermore, for the privacy security of VM scheduling, a safety-oriented energy-saving scheme based on information difference is proposed to ensure the dataset availability under privacy protection, comparing with $\varepsilon$ -differential privacy algorithm and $(\varepsilon, \delta)$ -differential privacy algorithm. Simulation results show that the safe energy-saving strategy can significantly reduce the energy consumption in CDCs with guaranteeing the security and availability of the important datasets.