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Web servers under overload: How scheduling can help

Published:01 February 2006Publication History
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Abstract

This article provides a detailed implementation study on the behavior of web serves that serve static requests where the load fluctuates over time (transient overload). Various external factors are considered, including WAN delays and losses and different client behavior models. We find that performance can be dramatically improved via a kernel-level modification to the web server to change the scheduling policy at the server from the standard FAIR (processor-sharing) scheduling to SRPT (shortest-remaining-processing-time) scheduling. We find that SRPT scheduling induces no penalties. In particular, throughput is not sacrificed and requests for long files experience only negligibly higher response times under SRPT than they did under the original FAIR scheduling.

References

  1. Abdelzaher, T. F. and Bhatti, N. T. 1999. Web content adaptation to improve server overload behavior. WWW8/Comput. Networks 31, 11-16, 1563--1577.]] Google ScholarGoogle Scholar
  2. Almesberger, W. Linux network traffic control---implementation overview. Available at http://lrcwww.epfl.ch/linux-diffserv/.]]Google ScholarGoogle Scholar
  3. Andresen, D. and Yang, T. 1997. Multiprocessor scheduling with client resources to improve the response time of WWW applications. In the International Conference on Supercomputing. 92--99.]] Google ScholarGoogle Scholar
  4. Arlitt, M. and Jin, T. 2000. Workload characterization of the 1998 world cup Web site. IEEE Network 14, 3, 30--37.]]Google ScholarGoogle Scholar
  5. Aron, M. and Druschel, P. 1999. TCP implementation enhancements for improving webserver performance. Tech. Rep. TR99-335, Rice University.]]Google ScholarGoogle Scholar
  6. Banga, G. and Druschel, P. 1999. Measuring the capacity of a web server under realistic loads. World Wide Web 2, 1-2, 69--83.]] Google ScholarGoogle Scholar
  7. Banga, G., Druschel, P., and Mogul, J. C. 1999. Resource containers: A new facility for resource management in server systems. In Proceedings of OSDI '99. 45--58.]] Google ScholarGoogle Scholar
  8. Bansal, N. and Harchol-Balter, M. 2001a. Analysis of SRPT scheduling: Investigating unfairness. In Proceedings of ACM SIGMETRICS '01.]] Google ScholarGoogle Scholar
  9. Bansal, N. and Harchol-Balter, M. 2001b. Scheduling solutions for coping with transient overload. Tech. rep. CMU-CS-01-134, Carnegie Mellon University.]]Google ScholarGoogle Scholar
  10. Barford, P. and Crovella, M. E. 1998. Generating representative Web workloads for network and server performance evaluation. In Proceedings of SIGMETRICS '98 (July) 151--160.]] Google ScholarGoogle Scholar
  11. Barford, P. and Crovella, M. E. 1999. A performance evaluation of hyper text transfer protocols. In Proceedings of ACM SIGMETRICS '99 (May) 188--179.]] Google ScholarGoogle Scholar
  12. Bender, M., Chakrabarti, S., and Muthukrishnan, S. 1998. Flow and stretch metrics for scheduling continuous job streams. In Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms.]] Google ScholarGoogle Scholar
  13. Bernstein, D. J. 1997. Syn cookies. http://cr.yp.to/syncookies.html.]]Google ScholarGoogle Scholar
  14. Bestavros, A., Carter, R. L., Crovella, M. E., Cunha, C. R., Heddaya, A., and Mirdad, S. A. 1995. Application-level document caching in the Internet. In Proceedings of the 2nd International Workshop on Services in Distributed and Networked Environments (SDNE'95) (June).]] Google ScholarGoogle Scholar
  15. Brakmo, L. and Peterson, L. 1995. Performance problems in 4.4 BSD TCP. ACM Comput. Comm. Rev. 25, 5.]] Google ScholarGoogle Scholar
  16. Braun, H. and Claffy, K. 1994. Web traffic characterization: An assessment of the impact of caching documents from NCSA's Web server. In Proceedings of the 2nd International WWW Conference.]]Google ScholarGoogle Scholar
  17. Cherkasova, L. and Phaal, P. 1998. Session-based admission control: A mechanism for improving the performance of an overloaded web server. Tech. Rep. HPL-98-119, Hewlett Packard Laboratories.]]Google ScholarGoogle Scholar
  18. Cockcroft, A. 1996. Watching your web server. The Unix Insider at http://www.unixinsider.com (April).]]Google ScholarGoogle Scholar
  19. Colajanni, M., Yu, P. S., and Dias, D. M. 1998. Analysis of task assignment policies in scalable distributed Web -server systems. IEEE Trans. Parall. Distrib. Syst. 9, 6, 585--699.]] Google ScholarGoogle Scholar
  20. Cooperative Association for Internet Data Analysis (CAIDA). 1999. Packet length distributions. http://www.caida.org/analysis/AIX/plen_hist.]]Google ScholarGoogle Scholar
  21. Crovella, M., Frangioso, R., and Harchol-Balter, M. 1999. Connection scheduling in web servers. In USENIX Symposium on Internet Technologies and Systems (Oct).]] Google ScholarGoogle Scholar
  22. Day, M., Cain, B., Tomlinson, G., and Rzewski, P. 2002. A model for content internetworking (cdi). Internet Draft (draft-ietf-cdi-model-02.txt) (May).]] Google ScholarGoogle Scholar
  23. Dias, D. M., Kish, W., Mukherjee, R., and Tewari, R. 1996. A scalable and highly available web server. In COMPCON. 85--92.]] Google ScholarGoogle Scholar
  24. Druschel, P. and Banga, G. 1996. Lazy receiver processing (LRP) : A network subsystem architecture for server systems. In Proceedings of OSDI '96 (Oct) 261--275.]] Google ScholarGoogle Scholar
  25. Elnikety, S., Nahum, E. M., Tracey, J., and Zwaenepoel, W. 2004. A method for transparent admission control and request scheduling in dynamic e-commerce Web sites. In International World-Wide Web Conference (WWW'04) (May) New York, NY.]] Google ScholarGoogle Scholar
  26. Feldmann, A. Web performance characteristics. IETF (Nov). http://www.research.att.com/anja/feldmann/papers.html.]]Google ScholarGoogle Scholar
  27. Friedman, E. J. and Henderson, S. G. 2003. Fairness and efficiency in web server protocols. In Proceedings of the ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems (May).]] Google ScholarGoogle Scholar
  28. Gong, M. and Williamson, C. 2003. Quantifying the properties of SRPT scheduling. In Proceedings of IEEE/ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS).]]Google ScholarGoogle Scholar
  29. Gwertzman, J. and Seltzer, M. 1994. The case for geographical push-caching. In Proceedings of HotOS '94 (May).]] Google ScholarGoogle Scholar
  30. Harchol-Balter, M., Schroeder, B., Agrawal, M., and Bansal, N. 2003. Size-based scheduling to improve web performance. ACM Trans. Comput. Syst. 21, 2 (May).]] Google ScholarGoogle Scholar
  31. Internet Town Hall. The Internet traffic archives. Available at http://town.hall.org/Archives/pub/ITA/.]]Google ScholarGoogle Scholar
  32. Internet Traffic Report. 2004. http://www.internettrafficreport.com.]]Google ScholarGoogle Scholar
  33. IRCache Home. 2004. The trace files. http://www.ircache.net/Traces/.]]Google ScholarGoogle Scholar
  34. Iyer, R., Tewari, V., and Kant, K. 2000. Overload control mechanisms for web servers. In Workshop on Performance and QoS of Next Generation Networks (Nov).]]Google ScholarGoogle Scholar
  35. Johnson, K. L., Carr, J. F., Day, M. S., and Kaashoek, M. F. 2000. The measured performance of content distribution networks. In Proceedings of the 5th International Web Caching and Content Delivery Workshop.]]Google ScholarGoogle Scholar
  36. Kaashoek, M., Engler, D., Wallach, D., and Ganger, G. 1996. Server operating systems. In SIGOPS European Workshop '96. 141--148.]] Google ScholarGoogle Scholar
  37. Krishnamurthy, B. and Rexford, J. 2001. Web Protocols and Practice: HTTP/1.1, Networking Protocols, Caching, and Traffic Measurement. Addison-Wesley.]] Google ScholarGoogle Scholar
  38. Krishnamurthy, B., Wills, C., and Zhang, Y. 2001. The use and performance of content distribution networks. In Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement.]] Google ScholarGoogle Scholar
  39. Kurose, J. and Ross, K. W. 2001. Computer Networking: A Top-Down Approach Featuring the Internet. Addison Wesley Longman, Inc.]] Google ScholarGoogle Scholar
  40. LeFebvre, W. 2002 Cnn.com: Facing a world crisis. The USENIX Technical Conference, (June).]]Google ScholarGoogle Scholar
  41. Maggs, B. Vice President of Research, 2001. Akamai Technologies. Personal communication.]]Google ScholarGoogle Scholar
  42. Manley, S. and Seltzer, M. 1997. Web facts and fantasy. In Proceedings of the 1997 USITS.]] Google ScholarGoogle Scholar
  43. McWherter, D., Schroeder, B., Ailamaki, A., and Harchol-Balter, M. 2004. Priority mechanisms for OLTP and transactional web applications. In the 20th International Conference on Data Engineering (ICDE'04).]] Google ScholarGoogle Scholar
  44. Microsoft TechNet Insights and Answer for IT Professional 2001. The arts and science of web server tuning with internet information services 5.0. http://www.microsoft.com/technet/.]]Google ScholarGoogle Scholar
  45. Mogul, J. C. 1995. The case for persistent-connection HTTP. In Proceedings of ACM SIGCOMM '95 (Oct). 299--313.]] Google ScholarGoogle Scholar
  46. Mogul, J. C. 1995. Network behavior of a busy Web server and its clients. Tech. Rep. 95/5, Digital Western Research Laboratory (Oct).]]Google ScholarGoogle Scholar
  47. Mogul, J. C. and Ramakrishnan, K. K. 1996. Eliminating receive livelock in an interrupt-driven kernel. In Proceedings of USENIX Technical Conference. 99--111.]] Google ScholarGoogle Scholar
  48. Murta, C. D. and Corlassoli, T. P. 2003. Fastest connection first: A new scheduling policy for web servers. In Proceedings of the 18th International Teletraffic Congress (ITC-18) (Sept).]]Google ScholarGoogle Scholar
  49. Nahum, E., Rosu, M., Seshan, S., and Almeida, J. 2001. The effects of wide-area conditions on www server performance. In Proceedings of ACM SIGMETRICS'01. 257--267.]] Google ScholarGoogle Scholar
  50. National Institute Standards and Technology. Nistnet. http://snad.ncsl.nist.gov/itg/nistnet/.]]Google ScholarGoogle Scholar
  51. Padhye, J., Firoiu, V., Towsley, D. F., and Kurose, J. F. 2000. Modeling tcp reno performance: A simple model and its empirical validation. IEEE/ACM Trans. Netw. 8, 2, 133--145.]] Google ScholarGoogle Scholar
  52. Pai, V. S., Druschel, P., and Zwaenepoel, W. 1999. Flash: An efficient and portable web server. In Proceedings of USENIX 1999 (June).]] Google ScholarGoogle Scholar
  53. Paxson, V. and Allman, M. 2000. Computing TCP's retransmission timer. RFC 2988, http://www.faqs.org/rfcs/rfc2988.html.]] Google ScholarGoogle Scholar
  54. Rai, I. A., Urvoy-Keller, G., and Biersack, E. 2003. Analysis of LAS scheduling for job size distributions with high variance. In Proceedings of the ACM Sigmetrics Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) (June).]] Google ScholarGoogle Scholar
  55. Rawat, M. and Kshemkayani, A. 2003. SWIFT: Scheduling in web servers for fast response time. In the 2nd IEEE International Symposium on Network Computing and Applications (April).]] Google ScholarGoogle Scholar
  56. Rizzo, L. 1997. Dummynet: A simple approach to the evaluation of network protocols. ACM Comput. Commun. Rev. 27, 1.]] Google ScholarGoogle Scholar
  57. Schrage, L. E. and Miller, L. W. 1966. The queue M/G/1 with the shortest remaining processing time discipline. Operations Resear. 14, 670--684.]]Google ScholarGoogle Scholar
  58. Seshan, S., Balakrishnan, H., Padmanabhan, V. N., Stemm, M., and Katz, R. 1998. TCP behavior of a busy internet server: Analysis and improvements. In Proceedings of the Conference on Computer Communications (IEEE Infocom). 252--262.]]Google ScholarGoogle Scholar
  59. Silberschatz, A., Galvin, P., and Gagne, G. 2002. Operating System Concepts, 6th Ed. John Wiley & Sons.]] Google ScholarGoogle Scholar
  60. Stallings, W. 2001. Operating Systems, 4th Ed. Prentice Hall.]]Google ScholarGoogle Scholar
  61. The World Wide Web Consortium (W3C). Libwww---the W3C protocol library. http://www.w3.org.]]Google ScholarGoogle Scholar
  62. Voigt, T. and Gunnigberg, P. 2001. Kernel-based control of persistent web server connections. ACM SIGMETRICS Performance Evaluation Review 29, 2, 20--25.]] Google ScholarGoogle Scholar
  63. Voigt, T., Tewari, R., Freimuth, D., and Mehra, A. 2001. Kernel mechanisms for service differentiation in overloaded web servers. In Proceedings of the USENIX Annual Technical Conference (June) Boston, MA.]] Google ScholarGoogle Scholar
  64. Welsh, M. and Culler, D. 2003. Adaptive overload control for busy internet servers. In Proceedings of the USENIX Symposium on Internet Technologies and Systems.]] Google ScholarGoogle Scholar
  65. Wierman, A. and Harchol-Balter, M. 2003. Classifying scheduling policies with respect to unfairness in an M/GI/1. In ACM Sigmetrics International Conference on Measurement and Modeling of Computer Systems.]] Google ScholarGoogle Scholar

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  1. Web servers under overload: How scheduling can help

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              Carlos Juiz

              The effectiveness of shortest remaining processing time (SRPT)-first scheduling for overloaded Web servers is shown in this paper. When servers overload, most solutions provide some dropping scheme to reach a stable performance state. The solution proposed here is based on connection scheduling without dropping requests. The authors confront FAIR scheduling with their proposal of the well-known SRPT (which gives unfair priority to requests for small files). Even though SRPT is not very original, what is new in this work is using SRPT as a solution for coping with the transient overload of servers. The authors make two contributions: they provide a detailed performance study of a Web server under persistent overload and transient overload, and they propose SRPT-like scheduling as a means to fight overload by improving mean response times up to an order of magnitude overall. Unfortunately, the paper focuses on static requests only, while Web sites are increasingly generating dynamic content. This subject must be approached in future studies of overloaded Web servers. The workload in the experiments discussed is based on a one-day trace from the 1998 Soccer World Cup, which is a slightly old trace, although the authors provide another simpler study of a trace from NASA Web servers. However, there is no additional information about the dates in which the study was performed. The authors show that SRPT scheduling alleviates three problems of Web servers: high queueing delays at the server due to high numbers of connections sharing the bandwidth, drops of signaling, and loss of packets inside the kernel of the server. This is an interesting work about Web server overloading. Understanding this topic is a necessary first step in understanding future implementations of other scheduling schemes for servers with static and dynamic traffic. Online Computing Reviews Service

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              • Published in

                cover image ACM Transactions on Internet Technology
                ACM Transactions on Internet Technology  Volume 6, Issue 1
                February 2006
                116 pages
                ISSN:1533-5399
                EISSN:1557-6051
                DOI:10.1145/1125274
                Issue’s Table of Contents

                Copyright © 2006 ACM

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                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 1 February 2006
                Published in toit Volume 6, Issue 1

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