Energy conservation policies for web servers

  • Authors:

  • Mootaz Elnozahy;Michael Kistler;Ramakrishnan Rajamony

  • Affiliations:

  • Low-Power Computing Research Center, IBM Research, Austin, TX;Low-Power Computing Research Center, IBM Research, Austin, TX;Low-Power Computing Research Center, IBM Research, Austin, TX

  • Venue:
  • USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
  • Year:
  • 2003

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Abstract

Energy management for servers is now necessary for technical, financial, and environmental reasons. This paper describes three policies designed to reduce energy consumption in Web servers. The policies employ two power management mechanisms: dynamic voltage scaling (DVS), an existing mechanism, and request batching, a new mechanism introduced in this paper. The first policy uses DVS in isolation, except that we extend recently introduced task-based DVS policies for use in server environments with many concurrent tasks. The second policy uses request batching to conserve energy during periods of low workload intensity. The third policy uses both DVS and request batching mechanisms to reduce processor energy usage over a wide range of workload intensities. All the policies trade off system responsiveness to save energy. However, the policies employ the mechanisms in a feedback-driven control framework in order to conserve energy while maintaining a given quality of service level, as defined by a percentile-level response time. We evaluate the policies using Salsa, a web server simulator that has been extensively validated for both energy and response time against measurements from a commodity web server. Three daylong static web workloads from real web server systems are used to quantify the energy savings: the Nagano Olympics98 web server, a financial services company web site, and a disk intensive web workload. Our results show that when required to maintain a 90th-percentile response time of 50ms, the DVS and request batching policies save from 8.7% to 38% and from 3.1% to 27% respectively of the CPU energy used by the base system. The two polices provide these savings for complementary workload intensities. The combined policy is effective for all three workloads across a broad range of intensities, saving from 17% to 42% of the CPU energy.