A key concern in utility computing is managing capacity so that application service providers (ASPs) and computing utilities (CUs) operate in a cost effective way. To this end, we propose a framework for applying inventory control to capacity management for utility computing. The framework consists of: conceptual foundations (e.g., establishing connections between concepts in utility computing and those in inventory control); problem formulations (e.g., what factors should be considered and how they affect computational complexity); and quality of service (QoS) forecasting, which is predicting the future effect on QoS of ASP and CU actions taken in the current period (a critical consideration in searching the space of possible solutions).

Utility computing provides a pay-as-you-go approach to information systems in which application providers (e.g., web sites) can better manage their costs by adding capacity in response to increased demands and shedding capacity when it is no longer needed. This paper addresses application providers who use clusters of servers. Our work develops a framework to determine the number of servers that minimizes the sum of quality-of-service (QoS) costs resulting from service level penalties and server holding costs for the server cluster. The server characteristics considered are service rate, failure rates, repair rates, and costs. The contributions of this paper are: 1) a model for the performance and availability of an e-Commerce system that is consistent with data from a multisystem testbed with an e-Commerce workload; 2) a business-oriented cost model for resource allocation for application providers; 3) a closed form approximation for the optimal allocation of servers for an application provider based on the performance model in 1) and the cost model in 2); and 4) a simple criteria for utility owners and server manufacturers to make tradeoffs between server characteristics.