Multi-Objective Virtual Machine Placement using Order Exchange and Migration Ant Colony System Algorithm

Abstract

Order Exchange and Migration Ant Colony System(OEMACS) and Ant Colony System OEMACS approach based on ACS that finds solutions by combining order exchange and migration local search strategies, was developed after examining the ant colony system's (ACS) promising performance for combinatorial issues. The ACO algorithm, which is regarded as best approach solving for virtual machine placement(VMP) problem, is capable of significantly reducing the number of active servers from a optimization standpoint. These bio-inspired algorithms help in solving VMP problem. Using the pheromone deposition method, artificial ants are guided to the feasible solution in ACO. It also arranges virtual machines in a way that reduces resource waste. This strategy is used on servers with homogeneous and heterogeneous VM sizes. The VMP is implemented using the ACO algorithm and OEMACS, and a comparison is drawn between them that shows their efficiency in terms of execution time and Energy Conserved.