A Study Of Parallel Data Mining In A Peer-To-Peer Network  

Oleh:

[s.n]

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Concurrent Engineering vol. 15 no. 3 (Sep. 2006), page 281-290.
Topik: parallel algorithm; peer-to-peer network; data mining; association rule mining; distributed computing; network applications.
Fulltext: 281.pdf (231.12KB)

Isi artikel

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.

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