Utility-based resource allocation for virtual machines in Cloud computing

Abstract

One of the challenges of Infrastructure-as-a-Service Clouds is how to dynamically allocate resources to virtual machines such that quality of service constraints are satisfied and operating costs are minimized. The tradeoff between these two conflicting goals can be expressed by a utility function. In this paper, a two-tier resource management approach based on adequate utility functions is presented, consisting of local controllers that dynamically allocate CPU shares to virtual machines to maximize a local node utility function and a global controller that initiates live migrations of virtual machines to other physical nodes to maximize a global system utility function. Experimental results show the benefits of the proposed approach in Cloud computing environments.