Abstract-This paper proposes to improve search i n unstructured peer-to-peer (PZP) overlay networks by building a partial index of shared data. The index maintains two types of information: the top interests of peers and globally unpopular data, both characterized by data properties. The proposed search protocol, assisted seurch with partial indexing, makes use of the index to improve search in three ways. First, the index assists peers to find other peers with similar interests and the unstructured search overlay is formed to reflect peer interests. Second, the index also provides search hints for those data difficult to locate by exploring peer interest locality, and these hints can be used for secondchance search. Third, the index helps to locate unpopular data items. Experiments based on both the W e b and P2P file sharing traces show that the assisted search with a lightweight partiat indexing service can significantly improve the success rate and search speed in locating data, while inducing less traffic overhead than Gnutella and a hit-rate based protocol in unstructured P2P Keywords: Peer-to-Peer, search, indexing I. INT.RODUCTION In the past few years peer-to-peer (P2P) applications have become popular. The most prevalent P2P application till today is file sharing. P2P file sharing systems have been constantly evolving, for example, from the pioneer Napster to Gnutella, to Kazza, etc. One major driving force behind this evolution is to strive €or better search mechanisms. The earliest search (i.e., Napster) was performed by a centralized server. This approach is obviously not scalable. The search protocol widely in use today involves flooding the P2P network. This decentralized approach is highly robust to failures or node transience. Since there is no explicit control over the network topology or data placement, these P2P networks are usually referred to as ''unstructured''. Tables (DHTs) , and search is performed by looking up the DHTs. In these "smctured" P2P networks, data items can be located in a small number of hops without incurring excessive overhead. More recently, DHTs have been proposed to implement multiple-keyword search [ 151 or full-text search 1241, [23]. In addition to the search algorithms, P2P file sharing systems also differ in whether they involve indexing of shared files. In the case of unstructured P2P networks, the earliest system, Napstet, maintained a full index of shared files in a centralized server. The now popular Gnutella-like networks do not implement global indexing and instead search in these networks relies on flooding. In P2P networks with super-peers. local-scale indices are maintained by more resourceful peers on behalf of other nearby peers. In structured P2P systems, inverted lists of documents are published to the DHT under single terms 1151. [231 or term (semantic) vectors [24]. Search is conducted by looking up the DHT-based index In summary, so far indexing either is required for all data items or does no1 exist at all in P2P file sharing systems. Besides, if indexing is performed. it is only used for searching. In this paper, we propose a DHT-based partial indexing scheme. Instead of indexing all data items owned by each peer, only a portion of them are registered with the index. The partial index has three complementary purposes. First, it helps peers to find shared interests. Peers are organized based on their interests in a similar way as proposed in t41, [20]. However. instead of accumulating the knowledge about other peers' interests from incremental search experience, peers can directly communicate through the index. Specifically, peers register their major interests (e.g., determined from data downloaded in the past) with the index and also query the index for other peers with similar interests. Peers that share common interests connect to each other as neighbors in the unstructured overlay. Because of the locality of interests. a query is more likely to be satisfied by nearby peers. Second, the index also provides search hints for those data difficult to locate even after interest-based clustering. We expect that L h h e majority of queries can be satisfied by looking up the unstructured search overlay created based on peer interests. For those queries that cannot be resolved, the index can be queried for search hints, Specifically, the index returns pointers to peers that have registered some of the properlies being searched for as their top interests. These possible destinations are used for second-chance search. Finally. the index helps to improve the chances of finding unpopular data, The success of search is closely related to data popularity. In existing unstructured P2P overlays like Gnutella, a popular data item is more likely to be located since there are more replicas in the network, whereas an unpopular data item can not be found unless a large number or all of the peers are searched, e.g., using expanding ring search with increasing TILS. In this paper, we explicitly address data popularity. Specifically, peers locally monitor the popularity of their own data, and unpopular data, in the form of data properties (keywords). are also registered with the index. During search, 1514 0-7803-8968-9/05/!320.00 (C>zOOS IEEE
Most peer-to-peer search systems REF [8] are proposed to establish intelligent search mechanism according to the node characters.
Assisted peer-to-peer search with partial indexing
Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies.
Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies.
Computer Science