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Satisfaction-Based Query Load Balancing

  • Jorge-Arnulfo Quiané-Ruiz
  • Philippe Lamarre
  • Patrick Valduriez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)

Abstract

We consider the query allocation problem in open and large distributed information systems. Provider sources are heterogeneous, autonomous, and have finite capacity to perform queries. A main objective in query allocation is to obtain good response time. Most of the work towards this objective has dealt with finding the most efficient providers. But little attention has been paid to satisfy the providers interest in performing certain queries. In this paper, we address both sides of the problem. We propose a query allocation approach which allows providers to express their intention to perform queries based on their preference and satisfaction. We compare our approach to both query load balancing and economic approaches. The experimentation results show that our approach yields high efficiency while supporting the providers’ preferences in adequacy with the query load. Also, we show that our approach guarantees interesting queries to providers even under low arrival query rates. In the context of open distributed systems, our approach outperforms traditional query load balancing approaches as it encourages providers to stay in the system, thus preserving the full system capacity.

Keywords

System Capacity Economic Approach Query Type Satisfaction Function Distribute Database System 
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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References

  1. 1.
    Azar, Y., Broder, A.Z., Karlin, A.R., Upfal, E.: Balanced Allocations. SIAM Journal on Computing (1999)Google Scholar
  2. 2.
    Buyya, R., Stockinger, H., Giddy, J., Abramson, D.: Economic Models for Management of Resources in Grid Computing. CoRR Journal (2001)Google Scholar
  3. 3.
    Feldman, M., Lai, K., Stoica, I., Chuang, J.: Robust Incentive Techniques for Peer-to-Peer Networks. In: Procs. of the EC ACM Conference (2004)Google Scholar
  4. 4.
    Ferguson, D., Nikolaou, C., Sairamesh, J., Yemini, Y.: Economic Models for Allocating Resources in Computer Systems. In: Market-based control: a paradigm for distributed resource allocation. World Scientific Publishing Company, Singapore (1996)Google Scholar
  5. 5.
    Ferguson, D., Yemini, Y., Nikolaou, C.: Microeconomic Algorithms for Load Balancing in Distributed Computer Systems. In: Procs. of the ICDCS Conference (1988)Google Scholar
  6. 6.
    Genova, Z., Christensen, K.: Challenges in URL Switching for Implementing Globally Distributed Web Sites. In: Procs. of the ICPP Workshops (2000)Google Scholar
  7. 7.
    Kamvar, S., Schlosser, M., Garcia-Molina, H.: The Eigentrust Algorithm for Reputation Management in P2P Networks. In: Procs. of the WWW Conference (2003)Google Scholar
  8. 8.
    Lamarre, P., Cazalens, S., Lemp, S., Valduriez, P.: A Flexible Mediation Process for Large Distributed Information Systems. In: Procs. of the CoopIS Conference (2004)Google Scholar
  9. 9.
    Li, L., Horrocks, I.: A Software Framework for Matchmaking Based on Semantic Web Technology. In: Procs. of the WWW Conference (2003)Google Scholar
  10. 10.
    Markatos, E.P.: Tracing a Large-Scale Peer to Peer System: An Hour in the Life of Gnutella. In: CCGRID Symposium (2002)Google Scholar
  11. 11.
    Mirchandaney, R., Towsley, D., Stankovic, J.: Adaptive Load Sharing in Heterogeneous Distributed Systems. Parallel and Distributed Computing Journal (1990)Google Scholar
  12. 12.
    Nodine, M., Bohrer, W., Ngu, A.: Semantic Brokering over Dynamic Heterogeneous Data Sources in InfoSleuth. In: Procs. of the ICDE Conference (1999)Google Scholar
  13. 13.
    Sah, A., Blow, J., Dennis, B.: An introduction to the Rush language. In: Procs. of the TCL Workshop (1994)Google Scholar
  14. 14.
    Saroiu, S., Gummadi, P.K., Gribble, S.: A Measurement Study of Peer-to-Peer File Sharing Systems. In: Procs. of the MCN Conference (2002)Google Scholar
  15. 15.
    Shivaratri, N., Krueger, P., Singhal, M.: Load Distributing for Locally Distributed Systems. Computer IEEE Journal (1992)Google Scholar
  16. 16.
    Stonebraker, M., Aoki, P., Litwin, W., Pfeffer, A., Sah, A., Sidell, J., Staelin, C., Yu, A.: Mariposa: A Wide-Area Distributed Database System. VLDB Journal (1996)Google Scholar
  17. 17.
    Sycara, K., Klusch, M., Widoff, S., Lu, J.: Dynamic Service Matchmaking Among Agents in Open Information Environments. In: SIGMOD Record (1999)Google Scholar
  18. 18.
    Zhu, H., Yang, T., Zheng, Q., Watson, D., Ibarra, O., Smith, T.: Adaptive Load Sharing for Clustered Digital Library Servers. In: HPDC Symposium (1998)Google Scholar
  19. 19.
    Özsu, T., Valduriez, P.: Principles of Distributed Database Systems, 2nd edn. Prentice-Hall, Englewood Cliffs (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jorge-Arnulfo Quiané-Ruiz
    • 1
  • Philippe Lamarre
    • 1
  • Patrick Valduriez
    • 1
  1. 1.INRIA and LINAUniversité de NantesNantes Cedex 3France

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