Improving Energy Efficiency for Mobile Media Cloud via Virtual Machine Consolidation
Mobile media applications are on the rise due to the explosive popularity of mobile devices. Advances in mobile media cloud (MMC) make it a promising solution to serve those huge multimedia applications. In MMC, virtualization is adopted to allocate resources elastically from a shared resource pool. Therefore, effective virtual machine (VM) consolidation is of paramount importance to maximize energy efficiency. In this paper, we consider a scenario that mobile media cloud performs video streaming and transcoding for viewers with different mobile devices. We formulate the VM consolidation problem as a mixed integer linear programming. Under this framework, the minimum energy consumption and the number of physical machines (PMs) in operation are derived. Based on these analytical results, for homogeneous media cloud, we develop an approximation algorithm for VM consolidation and placement which jointly considers CPU and bandwidth constraints. For heterogeneous media cloud, we derive an upper and a lower bound of the number of PMs and their energy consumption. Trace-driven simulations demonstrate that our proposed algorithm significantly reduces energy consumption and the number of PMs used.
mobile media cloud vm consolidation resource allocation