The Research On Content Searching, Locating, And Downloading Technologies In Peer-to-Peer Networks

With the wide application of the Internet and the continuously improved performance of the computer systems connected to the Internet, a new computing pattern, Peer-to-Peer computing, is booming. P2P computing devotes to sufficiently and reasonably organize and utilize the Internet edge's huge decentralized resources of computing, storage, communication and information. Since the introduction of Napster in 1999, P2P applications have become, only in a few years, one of the fastest growing and most popular Internet applications, which hold a huge number of users.Content service is one of the basic function modules of P2P systems. Content service application is one of the most important applications of P2P technology. How to implement efficient content service in a complex environment which contains decentralized and huge-amount users, uncontrollable nodes with unbalanced computing capacity and network connection is a challenging research area and of great importance.The research in this thesis focuses on content service in P2P network. It analyzes the particularity of content service in P2P network and the current research status on content service. In order to provide a flexible, efficient and extensible content service, we did much research on the key technologies for providing content service in P2P networks, including the construction of content service model, content searching techniques, content locationg techniques and content downloading techniques. This thesis makes key contributions to the following areas:1) A content service model based on content correlation is proposed. Based on the different requirements from the management of the original content and metadata, the model manages the storage, locating and downloading of original content in the content space, and it manages the storage of metadata, content correlating and content searching in the metadata space. In this model, the correlation among content is set up by the use of metadata, while the searching of content is based on the correlation of content.2) A search method—SBIS, based on interest similarity is proposed. SBIS computes the interest similarities among users by discovering the content correlations in the metedata space, and constructs logic connections among users with simliar interests. Search requests spread to friend nodes with similar interests with priority. When the content space is a structured P2P network, SBISS algorithm based on the particularity of structured P2P network is proposed to compute the interest similarities and the route search requests. Also SBISSG algorithm based on SBISS is proposed to integrate a new content grouping method without the need of users' descriptions and improves the extensibility of search algorithm and search quality. While the content space is an unstructured P2P network, SBISU algorithm based on the particularity of an...