An Energy-Aware Ant Colony Algorithm for Network-Aware Virtual Machine Placement in Cloud Computing

Abstract

The energy cost is one of the major concerns for the cloud providers. Virtual machine placement has been demonstrated as an effective method for energy saving. In addition to constraints caused by the physical machine resources such as CPU and memory (PM-constraints), the constraints caused by the network resource such as bandwidth (Net-constraints) are also crucial, since virtual machines are not isolated and require communication with each other to exchange data. However, most current research on data center power optimization only focuses on server resource. As a result, the optimization results are often inferior, because server consolidation without considering the network may cause traffic congestion and thus degraded network performance. We take the traffic demands between virtual machines into consideration and formulate the virtual machine placement problem under both PM-constraints and Net-constraints to minimize the energy cost, and propose an approach based on ant colony optimization to solve the problem. We evaluate the expected performance of our proposed algorithm through a simulation study, providing strong indications to the superiority of our proposed solution.