Using Proximity Information for Load Balancing in Geographically Distributed Web Server Systems

  • Dheeraj Sanghi
  • Pankaj Jalote
  • Puneet Agarwal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2510)


Many popular web sites get millions of hits everyday. To service a large number of requests, clusters of fully replicated web servers are used. In such a setup, the client’s request has to be directed to a cluster and then to a server within the cluster in a manner that the client receives the response in minimum time. In this paper, we propose an adaptive policy of selecting the nearest cluster for a request. Proximity is assessed by the round trip delay between the cluster and the client. An innovative idea is to measure this delay only for those clients who are sending a large number of requests. We have implemented this scheme, and using a test-bed which simulates the world wide web environment, compared the performance of the scheme with that of some existing schemes. The results indicate that the proposed scheme performs better, both in terms of average response time, as well as throughput.


Server Selection Round Robin Average Response Time Client Request Request Rate 
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.


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  1. [1]
    P. Agarwal. A test-bed for performance evaluation of load balancing strategies for web server systems. Master’s thesis, CSE Dept., IIT Kanpur, India, May 2001.Google Scholar
  2. [2]
    E. Anderson, D. Patterson, and E. Brewer. The Magicrouter: An application of fast packet interposing,, May 1996.
  3. [3]
    M. F. Arlitt and C. L. Williamson. Internet web servers: Workload characterization and performance implications. IEEE/ACM Trans. on Networking, 5(5):631–644, Oct. 1997.Google Scholar
  4. [4]
    M. Baentsh, L. Baum, and G. Molter. Enhancing the web’s infrastructure: From caching to replication. IEEE Internet Computing, l(2):18–27, March–April 1997.Google Scholar
  5. [5]
    M. Beck and T. Moore. The Internet-2 distributed storage infrastructure project: An architecture for Internet content channels. In Proc. of Third Int’l WWW Caching Workshop, Manchester, UK, June 1998.Google Scholar
  6. [6]
    V. Cardelini, M. Colajanni, and P. S. Yu. Dynamic load balancing on web server systems. IEEE Internet Computing, 3(3):28–39, May–June 1999.Google Scholar
  7. [7]
    M. Colajanni, P. S. Yu, and V. Cardelini. Dynamic load balancing on geographically distributed heterogenous web servers. In IEEE 18th Int’l Conference on Distributed Computing Systems, pages 295–302, May 1998.Google Scholar
  8. [8]
    M. E. Crovella and R. L. Carter. Dynamic server selection in the internet. In Proc. of the 3rd IEEE Workshop on the Architecture and Implementation of High Performance Communication Subsystems (HPCS’ 95), June 1995.Google Scholar
  9. [9]
    O. P. Damani, P. Y. Chung, and C. Kintala. ONE-IP: Techniques for hosting a service on a cluster of machines. In Proc. of 41st IEEE Computing Society Int’l Conference, pages 85–92, Feb. 1996.Google Scholar
  10. [10]
    Z. Fei, S. Bhattacharjee, E. W. Zegura, and M. Ammar. A novel server selection technique for improving the response time of a replicated service. In Proc. of IEEE INFOCOMM’ 98 Conf., 1998.Google Scholar
  11. [11]
    J. Guyton and M. Schwartz. Locating nearby copies of replicated internet servers. In Proceedings of ACM SIGCOMM’ 95 Conference, pages 288–298, Oct. 1995.Google Scholar
  12. [12]
    G. D. H. Hunt, G. S. Goldzsmit, R. P. King, and R. Mukherjee. Network dispatcher: A connection router for scalable internet services. In Proc. of 1th Int’l World Wide Web Conference, Apr. 1998.Google Scholar
  13. [13]
    T. T. Kwan, R. E. McGrath, and D. A. Reed. NCSA’s world wide web server: Design and performance. IEEE Computer, pages 68–74, Nov. 1995.Google Scholar
  14. [14]
    NIST. NistNet network emulator.
  15. [15]
    M. Sayal, Y. Breitbart, P. Scheuermann, and R. Vingralek. Selection algorithms for replicated web servers. In Proc. of the Workshop on Internet Server Performance, 1998.
  16. [16]
    C. Yoshilakawa, B. Chun, P. Eastham, A. Vahdat, T. Anderson, and D. Culler. Using smart clients to build scalable services. In Proc. of Usenix Ann. Tech. Conf., Anaheim, CA, Jan. 1997.Google Scholar
  17. [17]
    E. W. Zegura, M. H. Ammar, Z. Fei, and S. Bhattacharjee. Application-layer any-casting: A server selection architecture and use in a replicated service. IEEE/ACM Transactions on Networking, 8(4):455–466, Aug. 2000.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Dheeraj Sanghi
    • 1
  • Pankaj Jalote
    • 1
  • Puneet Agarwal
    • 1
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KanpurUPIndia

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