Comparative Analysis of File Transfer Algorithms to Reduce Average Download Time in Peer to Peer Networks

Abstract

File sharing using the peer-to-peer techniques are very effective and popular among Internet users. The peer-to-peer (P2P) network is used for downloading large-volume contents such as movies and software. To address the problem of flexibility and scalability, we propose a distributed peer-to-peer architecture and algorithms for data clustering. In general the file download can take more time depending on the level of network congestion or the service capacity fluctuations. In this paper we proposed distributed random chunk based periodic switching algorithm for file distribution. This algorithm remove the limitation of the existing systems i.e. Parallel downloading, Chunk based switching, periodic switching, dynamically distributed parallel periodic switching algorithm thus reduce the average download time. In this method corresponding file is divided into many small chunks, peers select their targets for downloading in a random fashion, thus increase the average download time in P2P networks and then analyze a simple, distributed algorithm to effectively remove these negative factors, thus minimizing the average download time.