This paper presents an energy management policy for reconfigurable clusters running a multi-tier application, exploiting DVS together with multiple sleep states. We develop a theoretical analysis of the corresponding power optimization problem and design an algorithm around the solution. Moreover, we rigorously investigate selection of the optimal number of spare servers for each power state, a problem that has only been approached in an ad-hoc manner in current policies.

This paper investigates the design issues and energy savings benefits of service prioritization in multi-tier Web server clusters. In many services, classes of clients can be naturally assigned different priorities based on their performance requirements. We show that if the whole multi-tier system is effectively prioritized, additional power and energy savings are realizable while keeping an existing cluster-wide energy management technique, through exploiting the different performance requirements of separate service classes. We find a simple prioritization scheme to be highly effective without requiring intrusive modifications to the system. In order to quantify its benefits, we perform extensive experimental evaluation on a real testbed. It is shown that the scheme significantly improves both total system power savings and energy efficiency, at the same time as improving throughput and enabling the system to meet per-class performance requirements.

The energy and cooling costs of Web server farms are among their main financial expenditures. This paper explores the benefits of dynamic voltage scaling (DVS) for power management in server farms. Unlike previous work, which addressed DVS on individual servers and on load-balanced server replicas, this paper addresses DVS in multistage service pipelines. Contemporary Web server installations typically adopt a three-tier architecture in which the first tier presents a Web interface, the second executes scripts that implement business logic, and the third serves database accesses. From a user's perspective, only the end-to-end response across the entire pipeline is relevant. This paper presents a rigorous optimization methodology and an algorithm for minimizing the total energy expenditure of the multistage pipeline subject to soft end-to-end response-time constraints. A distributed power management service is designed and evaluated on a real three-tier server prototype for coordinating DVS settings in a way that minimizes global energy consumption while meeting end-to-end delay constraints. The service is shown to consume as much as 30 percent less energy compared to the default (Linux) energy saving policy