Meta Heuristic Backtracking Algorithm for Virtual Machine Placement in Cloud Computing Migration

Cloud serves as a repository for voluminous data generated in internet. Situations prevailing before and after pandemic reveal the fact that cloud computing served as a backbone for almost all industries across the globe by its humongous computing facility. This necessitates numerous algorithms for the best usage of cloud resources namely virtual machines (VM). One such technique is our proposed meta heuristic Backtracking algorithm for finding an alternative place for VMs to be placed after migration from overloaded places. The performance metrics such as number of hosts shutdown, mean execution time and standard deviation of the execution time of the proposed meta heuristic Backtracking algorithm are compared against existing VM placement algorithms like Inter Quartile Range, Minimum Migration Time, Maximum Correlation and Random Selection, show a commendable improvement. The results show introducing meta heuristic techniques in a successful algorithm like Backtracking optimize the influential factors of Service Level Agreements (SLA) by increasing an 8% of total number of hosts shutdown, decreasing a 10.4% of time in mean execution time and decreasing a 33.5% of time in standard deviation of execution time.