Energy-aware Load Balancing in Heterogeneous Cloud Data Centers
Yongqiang Gao, Lei Yu · 2017
With the increasing popularity of cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of the cost of operating a cloud data centers. Therefore, energy-aware load balancing is increasingly becoming a core and challenging issue in cloud computing. In this paper, we propose an energy efficient load balancing algorithm which takes advantage of both dynamic voltage/frequency scaling and virtual machine consolidation to reduce energy consumed by cloud infrastructures. Our experimental results indicate that, compared to a round robin algorithm for load balancing in cloud computing, the proposed algorithm can achieve up to 35.3% energy saving in heterogeneous cloud data center.