Non-intrusive Performance Management for Computer Services

  • Magnus Karlsson
  • Christos Karamanolis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4290)


Networked computer services are increasingly hosted on shared consolidated physical resources (servers, storage, network) in data centers. Thus, some form of resource control is required to ensure contractual performance targets for service customers under dynamic workload and system conditions. This paper proposes a solution for resource control that maximizes the yield of the performance contracts given the available physical resources, while it does not require any modifications to the clients’ and the computing services’ software or hardware. Our approach achieves this by manipulating the flow of requests into the service by using one or more proxies between the clients and the service.

This paper evaluates Proteus, a prototype implementation of the proposed approach, on two different services: a 3-tier e-commerce system and a networked file service. We show that existing proxies for the two respective protocols (HTTP and NFS RPC) can easily be modified to use Proteus to schedule their requests. Once the modified proxies have been deployed, our approach is transparent to clients and services. Moreover, we show that, in contrast to prior art, our solution (1) is stable when workloads and systems change, (2) automatically tunes itself to different services, (3) can enforce flexible quality of service specifications, and (4) correctly detects and reacts to contention of internal service resources.


Performance Goal Performance Class Computer Service Share Ratio Latency Target 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Shenoy, P., Vin, H.: Cello: A Disk Scheduling Framework for Next Generation Operating Systems. In: International Conference on Measurement and Modelling of Computer Systems (SIGMETRICS), Madison, WI, pp. 44–55 (1998)Google Scholar
  2. 2.
    Voigt, T., Tewari, R., Freimuth, D., Mehra, A.: Kernel Mechanisms for Service Differentiation in Overloaded Web Servers. In: USENIX Annual Technical Conference, Boston, MA, pp. 189–202 (2001)Google Scholar
  3. 3.
    Shen, K., Tang, H., Yang, T., Chu, L.: Integrated resource management for cluster-based internet services. In: USENIX Symposium on Operating Systems Design and Implementation (OSDI), Boston, MA, pp. 225–238 (2002)Google Scholar
  4. 4.
    Abdelzaher, T., Shin, K.G., Bhatti, N.: Performance guarantees for web server end-systems: A control-theoretical approach. IEEE Transactions on Parallel and Distributed Systems 13(1), 80–96 (2002)CrossRefGoogle Scholar
  5. 5.
    Blanquer, J., Batchelli, A., Schauser, K., Wolski, R.: Quorum: Flexible Quality of Service for Internet Services. In: USENIX Symposium on Networked System Design and Implementation (NSDI), Boston, MA, pp. 159–174 (2005)Google Scholar
  6. 6.
    Chambliss, D., Alvarez, G., Pandey, P., Jadav, D., Xu, J., Menon, R., Lee, T.: Performance virtulization for large-scale storage systems. In: Symposium on Reliable Distributed Systems (SRDS), Florence, Italy, pp. 109–118 (2003)Google Scholar
  7. 7.
    Kamra, A., Misra, V., Nahum, E.: Yaksha: A Self-Tuning Controller for Managing the Performance of 3-Tiered Web sites. In: International Workshop on Quality of Service (IWQoS), Montreal, Canada, pp. 47–56 (2004)Google Scholar
  8. 8.
    Karlsson, M., Karamanolis, C., Zhu, X.: Triage: Performance isolation and differentiation for storage systems. In: International Workshop on Quality of Service (IWQoS), Montreal, Canada, pp. 67–74 (2004)Google Scholar
  9. 9.
    Lumb, C., Merchant, A., Alvarez, G.: Façade: Virtual storage devices with performance guarantees. In: International Conference on File and Storage Technologies (FAST), San Francisco, CA, pp. 131–144 (2003)Google Scholar
  10. 10.
    Karlsson, M., Karamanolis, C., Chase, J.: Controllable fair queuing for meeting performance goals. In: IFIP International Symposium on Computer Performance Modeling, Measurement and Evaluation (PERFORMANCE), Juan-les-Pins, France, pp. 278–294 (2005)Google Scholar
  11. 11.
    Chase, J., Anderson, D., Thakar, P., Vahdat, A., Doyle, R.: Managing Energy and Server Resources in Hosting Centres. In: ACM Symposium on Operating Systems Principles (SOSP), Banff, Canada, pp. 103–116 (2001)Google Scholar
  12. 12.
    Åström, K.J., Wittenmark, B.: Adaptive Control, 2nd edn. Electrical Engineering: Control Engineering. Addison-Wesley, Reading (1995)Google Scholar
  13. 13.
    Bryson, A., Ho, Y.C.: Applied Optimal Control – Optimization, Estimation, and Control. Taylor & Francis, Abington (1975)Google Scholar
  14. 14.
    Karlsson, M., Zhu, X., Karamanolis, C.: An Adaptive Optimal Controller for Non-Intrusive Performance Differentiation in Computing Services. In: IEEE Conference on Control and Automation (ICCA), Budapest, Hungary (2005)Google Scholar
  15. 15.
    Diao, Y., Hellerstein, J., Parekh, S.: MIMO control of an Apache web server: Modeling and controller design. In: American Control Conference (ACC), Anchorage, AK, pp. 4922–4927 (2002)Google Scholar
  16. 16.
    Li, B., Nahrstedt, K.: A control theoretical model for quality of service adaptations. In: International Workshop on Quality of Service (IWQoS), Napa, CA, pp. 145–153 (1998)Google Scholar
  17. 17.
    Lu, C., Abdelzaher, T., Stankovic, J., Son, S.: A feedback control approach for guaranteeing relative delays in web servers. In: IEEE Real Time Technology and Applications Symposium (RTAS), Taipei, Taiwan, pp. 51–62 (2001)Google Scholar
  18. 18.
    Robertsson, A., Wittenmark, B., Kihl, M., Andersson, M.: Design and Evaluation of Load Control in Web Server Systems. In: American Control Conference (ACC), Boston, MA, pp. 1980–1985 (2004)Google Scholar
  19. 19.
    Wei, J., Xu, C.Z.: A Self-tuning Fuzzy Control Approach for End-to-End QoS Guarantees in Web Servers. In: de Meer, H., Bhatti, N. (eds.) IWQoS 2005. LNCS, vol. 3552, pp. 123–135. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  20. 20.
    Diao, Y., Lui, X., Froehlich, S., Hellerstein, J., Parekh, S., Sha, L.: On-line response time optimization of an apache web server. In: Jeffay, K., Stoica, I., Wehrle, K. (eds.) IWQoS 2003. LNCS, vol. 2707, pp. 461–478. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  21. 21.
    Sundaram, V., Shenoy, P.: A practical learning-based approach for dynamic storage bandwidth allocation. In: Jeffay, K., Stoica, I., Wehrle, K. (eds.) IWQoS 2003. LNCS, vol. 2707, pp. 479–497. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  22. 22.
    Welsh, M., Culler, D.: Adaptive overload control for busy internet servers. In: USENIX Symposium on Internet Technologies and Systems (USITS), Seattle, WA, pp. 43–56 (2003)Google Scholar
  23. 23.
    Lu, Y., Abdelzaher, T., Lu, C., Tao, G.: An adaptive control framework for QoS guarantees and its application to differentiated caching services. In: International Workshop on Quality of Service (IWQoS), Miami Beach, FL, pp. 23–32 (2002)Google Scholar
  24. 24.
    Wu, K., Lilja, D., Bai, H.: The Applicability of Adaptive Control Theory to QoS Design: Limitations and Solutions. In: International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems (PMEO-PDS), Denver, CO (2005)Google Scholar
  25. 25.
    Liu, X., Zhu, X., Singhal, S., Arlitt, M.: Adaptive entitlement control of resource containers on shared servers. In: IFIP/IEEE International Symposium on Integrated Network Management (IM), Nice, France, pp. 163–176 (2005)Google Scholar
  26. 26.
    Lu, C., Wang, X., Koutsoukos, X.: End-to-end utilization control in distributed real-time systems. In: International Conference on Distributed Computing Systems (ICDCS), Hachioji, Japan, pp. 456–466 (2004)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2006

Authors and Affiliations

  • Magnus Karlsson
    • 1
  • Christos Karamanolis
    • 2
  1. 1.EneaStockholmSweden
  2. 2.VMware Inc.Palo AltoU.S.A.

Personalised recommendations