Comparison of workload consolidation algorithms for cloud data centers

Workload consolidation is an important method for the efficient operation of cloud data centers, impacting quality attributes such as resource utilization and power consumption. Many different approaches have been proposed workload consolidation, but few comparative studies were executed to date. Therefore, it unclear which work best in situation. In this article, we present a comprehensive simulation-based comparison five techniques. We introduce general framework techniques DISSECT-CF simulator foster development center algorithms. use evaluate effectiveness first fit decreasing heuristic, custom three population-based metaheuristics (genetic algorithm, artificial bee colony, particle swarm optimization). The evaluation based on wide variety real-world traces. algorithms are compared terms total energy consumption, duration simulation, number migrations. Based results, there no generally technique. results deliver insight into pros cons well impact parameters. particular, show that do not offer significant gain solution compensate increased simulation time.