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Since the emergence of peer to peer networks, search efficiency in such networks has been a matter of great concern, as it directly effects resource management of the network and influences users' satisfaction. In unstructured p2p networks, various search algorithms have been proposed so far that offer a tradeoff between scalability, congestion and user's satisfaction. In this paper, we survey newly introduced approaches to overcome search process problems. By reviewing these strategies and comparing them with previous search methods, we propose a new classification of informed search algorithms and we conclude that regarding this classification, informed search algorithms should be applied... 

In this paper, a new search algorithm in heterogeneous hierarchical unstructured p2p networks is presented which takes into account heterogeneity of peers such as upload bandwidth, life time in the network and process capacity in its peer discovery policy as factors that influence download performance and user satisfaction. One advantage of this algorithm is that it can be performed in a completely unstructured network without imposing any change on network topology and file replication. However, it obviously decreases file download time as it is designed to discover broad-bandwidth nodes with a higher probability. This property results in a fair distribution of load over heterogeneous p2p... 

We present an ontology based indexing method for unstructured P2P networks. We maintain limited size indexes at each node to identify number of documents accessible on each concept without loosing any indexing information. Out method supports complex queries, combined of conjunction and disjunction phrases. We simulate our search algorithm on an unstructured P2P network and show that our method significantly reduces the network traffic. © 2008 Springer-Verlag  

Effectiveness of P2P systems highly depends on efficiency of their search algorithms. With existence of malicious and dishonest nodes, reputation systems are essential to evaluate the trustworthiness of participating peers and to combat subversive peer behaviours. Surprisingly majority of the available reputation systems, ignore the underlying search algorithm and assume it pre-existing. In this paper we propose TBSearch, a robust and efficient trust based search algorithm for unstructured P2P networks. TBSearch maintains limited size routing indexes combining search and trust data, to guide queries to most reputable nodes. We introduce a low overhead method of estimating peers' reputation... 

Peer-to-peer networks (P2P) are beginning to form the infrastructure of future applications. One of the problems with unstructured P2P networks is their scalability limitation. This is also the problem in structured P2P networks that use broadcasting to find objects. These networks can't contain a large number of nodes because of the large amount of traffic that they have to handle. Local indexing is a method to reduce this traffic. But local indexes tend to become large with the growth of the network. Also limiting the size of these indexes causes loss of indexing information. In this paper we introduce a novel ontology based local index which limits the size of the local indexes without... 

Effectiveness of Peer-to-Peer (P2P) systems highly depends on efficiency and scalability of their search algorithms. Moreover, managing trust is a key issue for wide acceptance of P2P computing. Surprisingly, the majority of the available trust systems ignore the underlying search algorithm and assume it is preexisting. We claim that combining search and trust systems yields significant performance gains in terms of network traffic and query success rate. In this paper, we propose a robust and efficient trust based search framework for unstructured P2P networks. Our framework maintains limited size routing indexes combining search and trust data to guide queries to most reputable nodes. By...