On The Performance Of Content Delivery Under Competition In A Stochastic Unstructured Peer-To-Peer Network

In this paper, we investigate the impact of the interaction and competition among peers on downloading performance under stochastic, heterogeneous, unstructured P2P settings, thereby greatly extending the existing results on stochastic P2P networks made only under a single downloading peer in the network. To analyze the average download time in a P2P network with multiple competing downloading peers, we first introduce the notion of system utilization tailored to a P2P network.

We investigate the relationship between the average download time, system utilization and the level of competition among downloading peers in a stochastic P2P network. We then derive an achievable lower bound on the average download time and propose algorithms to give the peers the minimum average download time. Our result can much improve the download performance compared to earlier results in the literature.

Existing System:

Existing literature on the performance analysis of P2P-based file sharing applications in particular, we first provide a classification structure of performance issues in P2P-based file sharing that exploits different viewpoints that could be chosen to analyze the behavior of such applications. Furthermore, we discuss and summarize a subset of the proposals that are based on analytical and mathematical models of P2P-based file sharing applications. The P2P approach differs from the traditional client/server approach for building network applications since the participating hosts play dual roles as servers and clients.

This is because searching time is essential to the overall performance while the time spent on data transmission is short relative to that on large resources. For large-volume contents like multimedia documents or scientific data sets, the efficiency of the searching phase becomes a negligible factor to the overall performance while the data transfer efficiency becomes the key factor of the distribution efficiency. To effectively provide these new kind of services, developers of P2P-based applications need to guarantee that the systems reach performance levels similar to other more traditional approaches in terms not only of throughput and delay, but also of availability, stability, integrity and scalability, as well as security and trust.

Proposed System:

Peer-to-peer (P2P) technologies, such as Bit Torrent have been widely used for file transfer over the Internet. In those applications, file download time is one of the most important performance metrics. Theoretically, a P2P network can make its users download faster compared to a traditional client-server network because a P2P network is inherently scalable. Each node in a P2P network can act both as a server and a client simultaneously. As a result, the aggregate system service capacity increases with the number of downloading nodes in a P2P network It is widely believed that only the physical access bandwidth of each downloading peer can limit the download performance.

we investigate the impact of the interaction and competition among peers on downloading performance under stochastic, heterogeneous, unstructured P2P settings, thereby greatly extending the existing results on stochastic P2P networks made only under a single downloading peer in the network. To analyze the average download time in a P2P network with multiple competing downloading peers, we first introduce the notion of system utilization tailored to a P2P network.

We investigate the relationship between the average download time, system utilization and the level of competition among downloading peers in a stochastic P2P network. We then derive an achievable lower bound on the average download time and propose algorithms to give the peers the minimum average download time. Our result can much improve the download performance compared to earlier results in the literature.