Article thumbnail
Location of Repository

Knowledge based Replica Management in Data Grid Computation

By Riaz ul Amin and A. H. S. Bukhari


As the number of scientific disciplines has increased, the large data collections are emerging as important community resources. In domains as high energy physics, and computational genomic, the volume of interesting data is already measured in terabytes and will soon total peta bytes. The Research communities need to access and analyze this data using complex computational and access techniques. No data management infrastructure provides solution against the complex computational analysis of huge and geographically distributed data sets. Most of queries usually search analyzed data from terabytes of distributed data repository, over wide area networks. Replicas, and other advanced techniques collectively maximize the use of scarce storage, networking, and computing resources. Existing data grid replication technique no doubt provide us with availability of required data sets, but in order to create replica it has to bear an overhead of huge computation for required data sets. Large network traffic cause the performance unsatisfactory. Our goal in this effort is to provide users with replication infrastructure in Grid that uses Knowledgebase having learning capability so as to reduce the computation for creating dataset on each user request

Year: 2011
OAI identifier:

Suggested articles


  1. (2002). A Data Mining Architecture for Distributed Environments. IICS
  2. (2003). Decision Tree Construction for Data Mining on Clusters of Shared Memory Multiprocessors.
  3. (2003). Exploiting Parallelism in Decision Tree Induction.
  4. (2003). Facilities Management and E-business Model Application for Distributed Data Mining using Mobile Agents.
  5. Foster(The Data Grid towards architecture for distributed management and analyses of large scientific datasets)
  6. (2003). Globalization and Informatization: Analysis of the Application of Distributed Data Mining to Facilities Management.
  7. (2003). High-level Interfaces for Data Mining: From O_ine Algorithms on Clusters to Streams on Grids.
  8. (2011). Middleware Design for Computing Cluster to Process Satellite
  9. (1996). Parallel Mining of Association Rules. doi
  10. (2000). Scalable, Distributed and Dynamic Mining of Association Rules.
  11. (1998). The extensible markup language (xml) 1.0. W3C recomendation, World Wide Web Consortium,
  12. (2011). The Internet2 distributed storage infrastructure project: An architecture for internet content channels.
  13. (1998). The SDSC storage resource broker.
  14. (1997). The Stanford digital library metadata architecture.
  15. (2000). The Tao of e-Business Services,”
  16. (2011). TheWoRLD: Knowledge Discovery from Multiple Distributed Databases.
  17. (2004). TiVo: Making Show Recommendations Using a Distributed Collaborative Filtering Architecture.
  18. (1996). Towards interoperability in digital libraries.

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.