Advertisement

A Fair Load Balancing Algorithm for Hypercube-Based DHT Networks

  • Guowei Huang
  • Gongyi Wu
  • Zhi Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4505)

Abstract

Load balance is an important problem in the DHT-based P2P networks. In recent years, many solutions have been proposed to address this problem. However, these solutions have some limitations in our opinion. They either make some unrealistic assumptions about the network, or have high communication or maintenance overhead. In this paper, we present a distributed load balancing algorithm for the hypercube-based DHT networks. Our algorithm is based on the concept of fairness and uses the fairness index as the fairness metric. The purpose of our algorithm is to distribute the query load fairly to nodes. Each node periodically monitors the fairness index of current load distribution by using only local computation and it tries to achieve a fairer load distribution by dynamically adjusting its indegree according to its experienced load and the fairness index. The results of our experiments show that our algorithm has low overhead and it can achieve good load balance without unrealistic assumptions about the network.

Keywords

Load Balance Load Distribution Fairness Index Load Imbalance Virtual Server 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shen, H., Xu, C.: Elastic Routing Table with Probable Performance for Congestion Control in DHT Networks. In: Proceedings of the 26th International Conference on Distributed Computing Systems, ICDCS (2006)Google Scholar
  2. 2.
    Shen, H., Xu, C.: Hash-based Proximity Clustering for Load Balancing in Heterogeneous DHT Networks. In: Proceedings of the 20th IEEE International Parallel and Distributed Processing Symposium, IPDPS (2006)Google Scholar
  3. 3.
    Shen, H., Xu, C.: Locality-aware Randomized Load Balancing Algorithms for Structured P2P Networks. In: Proceedings of International Conference on Parallel Processing, ICPP (2005)Google Scholar
  4. 4.
    Drougas, Y., Kalogeraki, V.: A Fair Resource Allocation Algorithm for Peer-to-Peer Overlays. In: Proceedings of IEEE Conference on Computer Communications, INFOCOM (2005)Google Scholar
  5. 5.
    Zhu, Y., Hu, Y.: Efficient, Proximity-aware Load Balancing for DHT-based P2P Systems. IEEE Transactionson Parallel and Distributed Systems 16, 349–361 (2005)CrossRefGoogle Scholar
  6. 6.
    Zhao, B.Y., Huang, L., Stribling, J., Rhea, S.C., Joseph, A.D., Kubiatowicz, J.: Tapestry: An Infrastructure for Fault Tolerant Wide-area Location and Routing. IEEE Journal on Selected Areas in Communications 12, 41–53 (2004)CrossRefGoogle Scholar
  7. 7.
    Godfrey, B., Lakshminarayanan, K., Surana, S., Karp, R., Stoica, I.: Load balancing in Dynamic Structured P2P Systems. In: Proceedings of IEEE Conference on Computer Communications, INFOCOM (2004)Google Scholar
  8. 8.
    Stoica, I., Morris, R., Liben-Nowell, D., Karger, D.R., Kaashoek, M.F., Dabek, F., Balakrishnan, H.: Chord: A Scalable Peer-to-Peer Lookup Protocol for Internet Applications. IEEE/ACM Transactions on Networking 1, 17–32 (2003)CrossRefGoogle Scholar
  9. 9.
    Rao, A., Lakshminarayanan, K., Surana, S., Karp, R., Stoica, I.: Load balancing in Structured P2P Systems. In: Kaashoek, M.F., Stoica, I. (eds.) IPTPS 2003. LNCS, vol. 2735, pp. 68–79. Springer, Heidelberg (2003)Google Scholar
  10. 10.
    Gummadi, P.K., Dunn, R., Saroiu, S., Gribble, S.D., Levy, H., Zahorjan, J.: Measurement, Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload. In: Proceedings of the 19th ACM Symposium on Operation Systems Principles, SOSP (2003)Google Scholar
  11. 11.
    Saroiu, S., Gummadi, P.K., Gribble, S.D.: A Measurement Study of Peer-to-Peer File Sharing Systems. In: Proceedings of Multimedia Computing and Networking, MMCN (2002)Google Scholar
  12. 12.
    Rowstron, A., Druschel, P.: Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. In: Guerraoui, R. (ed.) Middleware 2001. LNCS, vol. 2218, p. 329. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  13. 13.
    Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S.: A Salable Content-addressable Network. In: Proceedings of the ACM SIGCOMM (2001)Google Scholar
  14. 14.
    Dabek, F., Kaashoek, M.F., Kaerger, D., Morris, R., Stocia, I.: Wide Area Cooperative Storage with CFS. In: Proceedings of the 18 th ACM Symposium on Operation Systems Principles, SOSP (2001)Google Scholar
  15. 15.
    Karger, D., Lehman, E., Leighton, T., Levine, M., Lewin, D., Panigrahy, R.: Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web. In: ACM Symposium on Theory of Computing (1997)Google Scholar
  16. 16.
    Jain, R., Chiu, D., Hawe, W.: A Quantitative Measure of Fairness and Discrimination for Resource Allocation in Shared Computer Systems. Technical Report, Digital Institution Corporation, Hudson (1984), http://www.cse.wustl.edu/~jain/papers/ftp/fairness.pdf

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Guowei Huang
    • 1
  • Gongyi Wu
    • 1
  • Zhi Chen
    • 1
  1. 1.Department of Computer Science, Nankai University, 300071 TianjinChina

Personalised recommendations