A genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks

Abstract

BitTorrent is a popular, open-source, hybrid peer-to-peer content distribution system that is conducive for distribution of large-volume contents. In this paper, we propose a genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks, which enhances the decision process performed at the tracker for transfer coordination. We also investigate how the strategy affects system throughput and distribution efficiency as well as peer contributions. We show through computer simulations that by increasing content availability to the clients from their immediate neighbors, it can significantly improve the system performance without trading off users' satisfaction. The proposed strategy can significantly improve the efficiency of distribution, especially for low-connectivity peers, and it is suitable to deploy for online decisions