The final experimental results have demonstrated that the MOGA-LS approach not only reduces the total incremental power consumption but also achieves a better load balancing while relatively maximizing the performance of live VM migration. That is, it has reduced the failure events of live VM migration and contributed to achieving better green Ixazomib Ki cloud data centers with load balancing.The rest of the paper is organized as follows. In Section 2, we present the related work, and the reasonable prerequisites are shown clearly. In Section 3, the main idea, design, problem formulation, solution representation, and implementation of MOGA-LS are introduced in details. In Section 4, the experimental results and analysis on CloudSim platform are given. Finally, in Section 5, we summarize the full paper, and future work is put forward.

2. Related WorkAs far as we know, the proposed problem which refers to finding a fit target host for a live VM migration according to the standard of minimizing the increment power consumption or load balancing has not been widely researched in the related fields of live VM migration policy let alone both. However, most researchers have focused on some problems which are similar to the proposed problem in this paper. Thus, the related work of the kind of problems relating to live VM migration towards power saving and load balancing will be discussed briefly in this section.Rusu et al. in [6] have presented a cluster-wide QoS-aware technique that dynamically reconfigures the cluster to reduce energy consumption during periods of reduced load.

The proposed system consists of two important components, namely, front end manager and a local manager. While the front end manager finds the servers which should be turned on or off in terms of a given system load, the local manager will utilize dynamic voltage and frequency scaling (DVFS) technique to conserve energy. The main shortage of the approach is the on/off policy. It relies on the table of values and needs offline computing. However, the system does not make use of server consolidation through VM migration, and thus, its on/off policy may not be much effective.Srikantaiah et al. [7] have investigated the problem of dynamic consolidation of applications serving small stateless requests in data centers to minimize the energy consumption. They modeled the problem as a multidimensional bin packing problem.

However, the proposed GSK-3 model doesn’t describe the degradation of performance due to the consolidation. Besides, the energy drawn may rely on a particular set of applications combined on a computer node. A heuristic for the defined bin packing problem is proposed by the authors. The heuristic is based upon the idea of minimizing the sum of the current allocations’ Euclidean distances to the optimal point at each server.