Latency and Energy-Aware Load Balancing in Cloud Data Centers: A Bargaining Game Based Approach

With the rapid surge in cloud services, cloud load balancing has become a paramount research issue. The major part of a cloud computing system's operational costs is attributed to energy consumption. Therefore, to provide better QoS, considering the energy minimization factor in load balancing is essential. This paper addresses the latency and energy-aware load balancing problem in a cloud computing system. Specifically, two fundamental performance criteria-response time and energy-for the load balancing problem are considered. To solve this problem, first, the load balancing problem is formulated as an optimization problem. Then it is modeled as a cooperative game so that the solution of the game, called the Nash bargaining solution (NBS), can simultaneously optimize both criteria. The existence and computation of NBS are analyzed theoretically, and an efficient algorithm, called Latency and Energy aWare load balancIng Scheme (LEWIS), is proposed to compute the NBS. Further, to assess the efficacy of LEWIS, it is compared with three other approaches, i.e., Coop RT, Coop EN, and NCG, on problem instances of various settings. The experimental results show that LEWIS not only provides less response time while consuming less energy but also gauntness fairness to the end-users.

Automated summary

This paper addresses the problem of latency and energy-aware load balancing in a cloud computing system. It formulates the problem as a cooperative game and proposes an efficient algorithm called LEWIS to compute the solution. Experimental results show that LEWIS not only reduces response time and energy consumption but also improves fairness to end-users.