A Multi-objective ACS Algorithm to Optimize Cost, Performance, and Reliability in the Cloud

In this paper, we present a novel Multi-Objective Ant Colony System algorithm to optimize Cost, Performance, and Reliability (MOACS-CoPeR) in the cloud. The proposed algorithm provides a metaheuristic-based approach for the multi-objective cloud-based software component deployment problem. MOACS-CoPeR explores the search-space of architecture design alternatives with respect to several architectural degrees of freedom and produces a set of Pareto-optimal deployment configurations. We also present a Java-based implementation of our proposed algorithm and compare its results with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). We evaluate the two algorithms against a cloud-based storage service, which is loosely based on a real system.