Topology-aware VM Placement for Network Optimization in Cloud Data Centers

Cloud data centers are hosting more and more complicated applications or services. This makes the network bandwidth becoming essential and critical for the normal application conduction or service provision. Hence, it is necessary to consider the network issue appropriately when deploying virtual machines (VMs) to avoid the network bottleneck and to guarantee the quality of services. In this paper, we focus on the VM placement problem for minimizing the maximal link utilization to avoid network congestion. We formulate the VM placement problem by representing the user requests with resource topologies, and prove the problem to be NP-hard. We present a heuristic algorithm based on the graph theory, which takes the resource topologies into account. The basic idea is to divide the requested VMs into servers with low network communication cost by analyzing the resource topology. We conduct extensive simulations, and the results show that our algorithm has a significant performance improvement on reducing network occupation compared to the best-fit strategy and divide-and-conquer strategy.