Blackbox prediction of the impact of DVFS on end-to-end performance of multitier systems

Performance Evaluation Review

Volumn 37, Issue 4, 2010, Pages 59-63

  Chen, Shuyi ^a   Joshi, Kaustubh R ^b   Hiltunen, Matti A ^b   Schlichting, Richard D ^b   Sanders, William H ^a  

^a University of Illinois at Urbana Champaign   (United States)

^b AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENERGY CONSERVATION; FORECASTING; LAPTOP COMPUTERS; SEMANTICS; VOLTAGE SCALING;

ACCURATE PREDICTION; APPLICATION SEMANTICS; DYNAMIC VOLTAGE AND FREQUENCY SCALING; END-TO-END PERFORMANCE; END-TO-END SERVICE; FREQUENCY GRADIENTS; MULTI-TIER APPLICATIONS; POTENTIAL IMPACTS;

DYNAMIC FREQUENCY SCALING;

EID: 79952013626     PISSN: 01635999     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1773394.1773404     Document Type: Conference Paper

References (14)

1. EPA Report on Server and Data Center Energy Efficiency, Aug 2007. http://www.energystar.gov/ia/partners/prod development/downloads/ EPA Datacenter Report Congress Final1.pdf.
2. The psychology of web performance, May 2008. http://www.websiteoptimization.com/speed/tweak/psychology-web-performance/.
3. Bhulai, S., Sivasubramanian, S., van der Mei, R., and van Steen, M. Modeling end-to-end response times in multitier Internet applications. Man. Traffic Perf. in Converged Networks 4516 (2007), 519-532.
4. Bodik, P., Sutton, C., Fox, A., Patterson, D., and Jordan, M. Response-time modeling for resource allocation and energy-informed SLAs. In Proc. Workshop on Statistical Learning Techniques for Solving Systems Problems (MLSys) (2007).
5. Castro-Leon, E. Musings about data center energy usage, Sept 2008. http://communities.intel.com/openport/community/openportit/ipip/blog/2008/09/07/ musings-about-data-center-energy-usage.
6. Ceaparu, I., Lazar, J., Bessiere, K., Robinson, J., and Shneiderman, B. Determining causes and severity of end-user frustration. Int. Journal of Human-Computer Interaction 17, 3 (2004), 333-356.
7. Cecchet, E., Marguerite, J., and Zwaenepoel, W. Performance and scalability of EJB applications. In Proc. OOPSLA'02 (2002), pp. 246-261.
8. Chen, S., Joshi, K., Hiltunen, M., Sanders, W., and Schlichting, R. Link gradients: Predicting the impact of network latency on multitier applications. In Proc. INFOCOM (Apr. 2009).
9. Farber, D. Google's Marissa Mayer: Speed wins. ZDNet Between the Lines, Nov. 2006. Accessed Apr. 2009. http://blogs.zdnet.com/BTL/?p=3925.
10. Galletta, D., Henry, R., McCoy, S., and Polak, P. Web site delays: How tolerant are users? J. of the Assoc. for Information Sys. 5, 1 (2004), 1-28.
11. Horvath, T., Abdelzaher, T., Skadron, K., and Liu, X. Dynamic voltage scaling in multitier web servers with end-to-end delay control. IEEE Trans. on Comp. 56, 4 (July 2006), 444-458.
12. Stewart, C., and Shen, K. Performance modeling and system management for multi-component online services. In Proc. NSDI (2005), vol. 2, pp. 71-84.
13. Urgaonkar, B., Pacifici, G., Shenoy, P., Spreitzer, M., and Tantawi, A. An analytical model for multi-tier internet services and its applications. In Proc. ACM SIGMETRICS (2005), pp. 291-302.
14. Woodside, M., Neilson, J., Petriu, D., and Majumdar, S. The stochastic rendezvous network model for performance of synchronous client-server-like distributed software. IEEE Trans. on Comp. 44, 1 (1995), 20-34.