An Online, Business-Oriented Optimization of Performance and Availability for Utility Computing

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 [24]. This paper develops a framework for Application Providers using a cluster design 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. The server characteristics considered are service rate, failure rates, repair rates, and costs. We further devise a simple approach for owners of computing utilities to select among servers with different characteristics and for server manufacturers to address design trade-offs between server characteristics. Our approach uses a performance and availability model that extends the M/M/m/K/M queueing system with considerations for failures and repairs. The model is validated with data from a product level testbed with an eCommerce workload. We develop a closed-form approximate solution for the optimal number of servers that works well for a wide range of system parameters. This result indicates that the optimal number of servers m* is the effective traffic intensity (the number of servers consumed by the workload with considerations for failures and repairs) with an adjustment for QoS costs and server holding costs. Last, we show that the Application Provider cost at m* is an increasing function of v, the effective server price performance (which considers failures and repairs). Thus, we propose that utility owners should consider v in their purchasing decisions, and manufacturers of servers should assess design trade-offs in terms of their impact on v.

By: Joseph Hellerstein, Kaan Katircioglu, Maheswaran Surendra

Published in: RC23325 in 2003


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