An efficient fault tolerance scheme based enhanced firefly optimization for virtual machine placement in cloud computing

The virtual machine placement for the highly reliable cloud application is considered as one of the challenging and critical issues. To tackle such an issue, this article proposes the enhanced firefly algorithm based virtual machine placement model. But the migration time of the virtual machine placement is high and to reduce the migration time of the virtual machine placement, this article utilizes the K-means clustering algorithm. In addition, to obtain the optimal cluster for the virtual machine placement, the adaptive particle swarm optimization with the coyote optimization algorithm is employed. The experimental results are conducted for the proposed approach using various measures such as transmission overhead, total execution time, packet size, parallel applications numbers, and virtual machine numbers. The results demonstrate that the proposed method offers improved performance and an optimal virtual machine placement scheme with respect to the various constraint factors. The evaluation exposes that the proposed method offers less execution time when compared to other methods.