Advertisement

An Efficient Load-Sharing and Fault-Tolerance Algorithm in Internet-Based Clustering Systems

  • In-Bok Choi
  • Jae-Dong Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)

Abstract

This paper proposes an efficient algorithm for load-sharing and fault-tolerance in Internet-based clustering systems. The algorithm creates a global scheduler based on the Weighted Factoring algorithm. And it applies an adaptive granularity strategy and the refined fixed granularity algorithm for better performance. It may also execute a partial job several times for fault-tolerance. For the simulation, the matrix multiplication using PVM is used in a Internet-based clustering system. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 55%, 63% and 20%, respectively. Also, this paper shows that it can process the fault-tolerance.

Keywords

Execution Time Transfer Time Partial Result Cluster System Master Node 
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.

References

  1. 1.
    Goo, B.-G.: Refined fixed granularity algorithm on Networks of Workstations. KIPS 8(2) (2001)Google Scholar
  2. 2.
    Hummel, S.F., Schmidt, J., Uma, R.N., Wein, J.: Load-Sharing in Heterogeneous Systems via Weighted Factoring. In: SPAA (1997)Google Scholar
  3. 3.
    Kee, Y., Ha, S.: A Robust Dynamic Load-Balancing Scheme for Data Parallel Application on Message Passing Architecture. In: PDPTA 1998, vol. II, pp. 974–980 (1998)Google Scholar
  4. 4.
    Kim, J.-S., Shim, Y.-C.: Space-Sharing Scheduling Schemes for NOW with Heterogeneous Computing Power. KISS 27(7) (2000)Google Scholar
  5. 5.
    Piotrowski, A., Dandamudi, S.: A Comparative Study of Load Sharing on Networks of Workstations. In: Proc. Int. Conf. Parallel and Distributed computing system, New Orleans (October 1997)Google Scholar
  6. 6.
    Shao, G.: Adaptive Scheduling of Master/Worker Applications on Distributed Computational Resources, Ph.D. thesis, UCSD (June 2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • In-Bok Choi
    • 1
  • Jae-Dong Lee
    • 1
  1. 1.Division of Information and Computer ScienceDankook UniversitySeoulKorea

Personalised recommendations