Advertisement

Dynamic Strategy of Placement of the Replicas in Data Grid

  • Ghalem Belalem
  • Farouk Bouhraoua
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4671)

Abstract

Grid computing is a type of parallel and distributed systems, that is designed to provide pervasive and reliable access to data and computational resources over wide are network. Data Grids connect a collect of geographically distributed computers and storage resources located in different parts of the world to facilitate sharing of data and resources. These grids are concentrated on the reduction of the execution time of the applications that require a great number of processing cycles by the computer. In such environment, these advantages are not possible unless by the use of the replication. This later is considered as an important technique to reduce the cost of access to the data in grid. In this present paper, we present our contribution to a cost model whose objective is to reduce the cost of access to replicated data. These costs depend on many factors like the bandwidth, data size, network latency and the number of the read/ write operations.

Keywords

Data Grid Replication Data placement Cost model CERN 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Deris, M.M., Abawajy, J.H., Suzuri, H.M.: An Efficient Replicated Data Access Approach for Large-Scale Distributed Systems, IEEE International Symposium CCGrid 2004, Chicago, Illinois, USA (April 19-22, 2004)Google Scholar
  2. 2.
    Goel, S., Sharda, H., Taniar, D.: Replica Synchronization in Grid Databases. Int. Journal Web and Grid Services 1(1), 87–112 (2005)CrossRefGoogle Scholar
  3. 3.
    The European Organization for Nuclear Physics CERN DataGrid Project, http://grid.web.cern.ch/grid/
  4. 4.
    Foster, I., Kesselman, C., Tuecke, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. Int. Journal Supercomputer Applications 15(3) (2003)Google Scholar
  5. 5.
    Lamehamedi, H., Szymanski, B., Deelman, E.: Data Replication Strategies in Grid Environments. In: Proc. 5th International Conference on Algorithms and Architecture for Parallel Processing, ICA3PP 2002, Bejing, China, pp. 378–383 (2002)Google Scholar
  6. 6.
    Leiserson, C.H.: Fat-Trees: Universal Networks for Hardware-Efficient Supercomputing. IEEE Trans. on Comp. C-34(10), 892–901 (1985)Google Scholar
  7. 7.
    NS Network Simulator, http://www.mash.cs.berkeley.edu/ns
  8. 8.
    Parhamu, B.: Introduction to Parallel Processing: Algorithms and Architectures, Plenum (1999)Google Scholar
  9. 9.
    Raynal, M.: Gestion des Donnees Reparties: Problemes et Protocoles. Tome3: Introduction aux principes des systemes repartis, Eyrolles, France (1992)Google Scholar
  10. 10.
    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, Heidelberg (1996)zbMATHGoogle Scholar
  11. 11.
    Xu, J., Li, B., Lun Lee, D.: Placement Problems for Transparent Data Replication Proxy Services. IEEE Journal on Selected Areas in Communications 20(7) (September 2002)Google Scholar
  12. 12.
    Milojicic, D.: Peer to Peer Technology, HP Labs Technical Report, HPL-2002-57, http://www.hpl.hp.com/techreports/2002/HPL-2002-57.html
  13. 13.
    Guyton, J.D., Michael, F.S.: Locating Nearby Copies of Replicated Internet Servers, University of Colorado, TR CU-CS-762-95Google Scholar
  14. 14.
    Ranganathan, K., Foster, I.: Identifying Dynamic Replication Strategies for a High Performance Data Grid. In: Proc. of the International Grid Computing Workshop, Denver, CO (November 2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ghalem Belalem
    • 1
  • Farouk Bouhraoua
    • 2
  1. 1.Dept. of Computer Science, Faculty of Sciences, University of Oran - Es Senia, OranAlgeria
  2. 2.Institute of Computer Science, Faculty of Science and Engineering, University of MostaganemAlgeria

Personalised recommendations