A Study of Parallel Data Mining in a Peer-to-Peer Network

Abstract

In this article, a parallel data mining algorithm in a distributed Peer-to-Peer (P2P) network is designed and proposed. The algorithm has the following advanced features: the implementation of the algorithm for all nodes in a P2P network is the same which satisfies not only the distribution but also the random walking in/out features of a P2P network; it balances the working load of each node in the P2P network well; it is easy for the maintenance and reuse of the codes. All processes of this algorithm are executed in parallel over a P2P network to reach high efficiency, fine scalability and efficient communication. Data mining for large and distributed databases in P2P networks requires more efficient parallel or distributed algorithms. Dealing with a fast changing P2P environment also demands more flexible and scaleable methods. Our parallel algorithm provides a good solution. Parallel P2P data mining applications may play a key role in the next generation of distributed database networks, file sharing networks, and search engines.