Optimizing Utility in Cloud Computing through Autonomic Workload Execution
Norman W. Paton, Marcelo A. T. Aragão, Kevin Lee, Alvaro A. A. Fernandes, Rizos Sakellariou · Murdoch Research Repository (Murdoch University) · 2009
Cloud computing provides services to potentially numerous remote users with diverse requirements. Al-though predictable performance can be obtained through the provision of carefully delimited services, it is straightforward to identify applications in which a cloud might usefully host services that support the composition of more primitive analysis services or the evaluation of complex data analysis requests. In such settings, a service provider must manage complex and unpredictable workloads. This paper describes how utility functions can be used to make explicit the desirability of different workload evalu-ation strategies, and how optimization can be used to select between such alternatives. The approach is illustrated for workloads consisting of workflows or queries. 1