Integration of Scheduling and Replication in Data Grids

  • Anirban Chakrabarti
  • R. A. Dheepak
  • Shubhashis Sengupta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3296)


Data Grids seek to harness geographically distributed resources for large-scale data-intensive problems. Such problems involve loosely coupled jobs and large data sets distributed remotely. Data Grids have found applications in scientific research fields of high-energy physics, life sciences etc. as well as in the enterprises. The issues that need to be considered in the Data Grid research area include resource management for computation and data. Computation management comprises scheduling of jobs, scalability, and response time; while data management includes replication and movement of data at selected sites. As jobs are data intensive, data management issues often become integral to the problems of scheduling and effective resource management in the Data Grids. The paper deals with the problem of integrating the scheduling and replication strategies. As part of the solution, we have proposed an Integrated Replication and Scheduling Strategy (IRS) which aims at an iterative improvement of the performance based on the coupling between the scheduling and replication strategies. Results suggest that, in the context of our experiments, IRS performs better than several well-known replication strategies.


Schedule Strategy Data Grid Queue Size Replication Strategy Data Replication 
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.
    Chervenak, Foster, I., Kesselman, C., Salisbury, C., Tuecke, S.: The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Datasets. Journal of Network and Computer Applications 23, 187–200 (2001)CrossRefGoogle Scholar
  2. 2.
    Beck, M., Moore, T.: The Internet2 distributed storage infrastructure project: An architecture for internet content channels. Computer Networking and ISDN Systems (1998)Google Scholar
  3. 3.
    Foster, Kasselman, C.: The Grid 2: Blueprint for a new Computing Infrastructure. Morgan Kaufman, San Francisco (2004)Google Scholar
  4. 4.
    Casanova, H., Obertelli, G., Berman, F., Wolski, R.: The AppLeS Parameter Sweep Template: User-Level Middleware for the Grid. In: Proc. SuperComputing 2000 (2000)Google Scholar
  5. 5.
    Banino, C., Beaumont, O., Carter, L., Ferrante, J., Legrand, A., Robert, Y.: Scheduling Strategies for Master-Slave tasking for Heterogeneous Processor Platforms. IEEE Trans. On Parallel and Distributed Systems 15(4) (April 2004)Google Scholar
  6. 6.
    Ranganathan, K., Foster, I.: Identifying Dynamic Replication Strategies for a High Performance Data Grid. In: Proc. Second IWGC (2001)Google Scholar
  7. 7.
    Thain, D., Bent, J., Arpaci-Dusseau, A., Arpaci-Dusseau, R., Livny, M.: Gathering at the Well: Creating Communities for Grid I/O. In: Proc. SuperComputing 2001 (2001)Google Scholar
  8. 8.
    Ranganathan, K., Foster, I.: Simulation Studies of Computation and Data Scheduling Algorithms for Data Grids. Journal of Grid Computing 1(2) (April 2003)Google Scholar
  9. 9.
    Mettu, R.R., Plaxton, K.G.: The Online Median Problem. SIAM Journal on Computing 32(3), 816–832 (2003)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Bell, W.H., Cameron, D.G., et al.: Simulation of Dynamic Grid Replication Strategies in OptorSim. In: Parashar, M. (ed.) GRID 2002. LNCS, vol. 2536, pp. 46–57. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  11. 11.
    Bell, W.H., Cameron, D.G., Carvajal-Schiaffino, R., Millar, A.P., Stockinger, K., Zini, F.: Evaluation of an Economy-Based File Replication Strategy for a Data Grid. In: Proc. CCGrid (May 2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Anirban Chakrabarti
    • 1
  • R. A. Dheepak
    • 1
  • Shubhashis Sengupta
    • 1
  1. 1.Software Engineering and Technology LaboratoryInfosys Technologies LtdBangaloreIndia

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