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
${{\sf L}}$
atency and
${{\sf E}}$
nergy a
${{\sf W}}$
are load balancIng
${{\sf S}}$
cheme (
${{\sf LEWIS}}$
), is proposed to compute the NBS. Further, to assess the efficacy of
${{\sf LEWIS}}$
, it is compared with three other approaches, i.e.,
${\mathsf {Coop\_{RT}}}$
,
${\mathsf {Coop\_{EN}}}$
, and
${\mathsf {NCG}}$
, on problem instances of various settings. The experimental results show that
${{\sf LEWIS}}$
not only provides less response time while consuming less energy but also gauntness fairness to the end-users.