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A Class based Piece Selection for Multi-Dimensional Aggregated Data Distribution in Peer to Peer Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 57 - Number 12 |
| Year of Publication: 2012 |
| Authors: N. T. Renukadevi, P. Thangaraj |
10.5120/9165-3557
|
N. T. Renukadevi, P. Thangaraj . A Class based Piece Selection for Multi-Dimensional Aggregated Data Distribution in Peer to Peer Network. International Journal of Computer Applications. 57, 12 ( November 2012), 9-12. DOI=10.5120/9165-3557
Abstract
A peer-to-peer (P2P) is a distributed application architecture, where each computer (node) in the net acts as a client/ server for the other nodes in the network. It allows sharing right to different sources and partitions tasks or workloads among peers. All the peers are equally privileged participants in the application. The searching performance, query expressivity, multi-dimensional distributed indexing are the emerging aspects of P2P. Its popularity is due to its scalability and distribution of large files efficiently without undue pressure on the origin server. In this work, it is proposed to investigate the performance of P2P networking when used to store multidimensional compressed aggregated data which can be used to download required data based on the query rather than downloading the entire database. For real-time query from users the specific pieces should be downloaded based on the query. To achieve this goal, it is critical to efficiently schedule the order in which pieces of the desired data are downloaded. Simply downloading pieces in sequential (earliest-first) order is prone to bottlenecks. Consequently it is proposed to implement aggregated class based scheduling ensuring high piece diversity while at the same time prioritizing pieces needed to maintain uninterrupted download based on query
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