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

Abstract

Cloud computing is one among the most crucial commercial technologies nowadays. It offers a diverse range of services. One of the most exciting and important procedures in cloud computing is virtual machine installation (VMP). Virtual Machine Placement uses evolutionary computing to lower energy consumption while lowering the total number of physical servers that are currently in use. By examining the ant colony system’s (ACS) promising performance for combinatorial issues, Order Exchange and Ant Colony System OEMACS, an approach based on ACS finds solution by combining order exchange and migration local search strategies, was developed (Order exchange and Migration Ant Colony System). From a global optimization standpoint, The OEMACS algorithm is capable of significantly lowering the active servers in number and is used for virtual machine assignment. It also aids in the reduction of the number of active servers that are underutilized. In OEMACS, artificial ants are guided to the best feasible solution using the pheromone deposition method. It also arranges virtual machines in such a way that resource waste and power consumption are reduced. On servers with homogenous and heterogeneous VM sizes, this strategy is used. OEMACS surpasses some of the previously utilized algorithms, such as standard heuristics and other evolutionary-based techniques, according to the findings.