Peer Selection in Peer-to-Peer Networks with Semantic Topologies

Haase, Peter; Siebes, Ronny; Harmelen, Frank van

doi:10.1007/978-3-540-30145-5_7

Cited by 76 publications

(65 citation statements)

References 17 publications

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“…From this set of ranked peers one can, for example, select the best n peers, or all peers whose rank value is above a certain threshold etc. A peer selection algorithm (Haase and Siebes, 2004) is also presented that allows a recommender system peer to select a set of other peers to cooperate with. The algorithm selection mechanism not only ensures a high degree of user satisfaction to the generated recommendation, it also makes sure that every peer behavior has been fairly absorbed.…”

Section: Peer Rank and Selection Algorithmmentioning

confidence: 99%

Improving the Performance of the Peer to Peer Network by Introducing an Assortment of Methods

Sendil¹,

Nagarajan²

2011

Journal of Computer Science

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Problem Statement: Peer to Peer (P2P) systems have grown dramatically in recent years. The most popular type of P2P systems are file sharing networks, which are used to share various types of content over the Internet. Due to the increase in popularity of P2P systems, the network performance of these systems has become a very important issue in the design and realization of these networks. Hence, the performance of the P2P has been improved. Approach: This paper suggests the following methods for the improving the performance of P2P systems: Method-1: Improving the P2P routing using a sandwich technique. Method-2: Improving the search performance by introducing a new searching method based on the super peer. Method-3: Improving the search by introducing a ranking algorithm based on the knowledge database. Results: The system demonstrates that the methods introduced here have improved the performance of P2P network efficiently when compared to the existing methodologies. Conclusions / Recommendations: The performance of the P2P systems have improved by using the above said methods, hence the traffic can be reduced in P2P network.

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Section: Peer Rank and Selection Algorithmmentioning

confidence: 99%

Improving the Performance of the Peer to Peer Network by Introducing an Assortment of Methods

Sendil¹,

Nagarajan²

2011

Journal of Computer Science

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“…Haase et al [13] describe another semantic P2P topology focused on efficiency. The authors start from a completely random network topology and eventually derive a topology that closely matches the similarity in the semantic knowledge of peers.…”

Section: Semantic P2p Topologiesmentioning

confidence: 99%

Probabilistic Discovery of Semantically Diverse Content in MANETs

Nedos

Singh

Cunningham

et al. 2009

IEEE Trans. on Mobile Comput.

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Abstract-Mobile ad hoc networks rely on the opportunistic interaction of autonomous nodes to form networks without the use of infrastructure. Given the radically decentralised nature of such networks, their potential for autonomous communication is significantly improved when the need for a priori consensus amongst the nodes is kept to a minimum. This paper addresses an issue within the domain of semantic content discovery, namely, its current reliance on the preexisting agreement between the schema of content providers and consumers. We present OntoMobil, a semantic discovery model for ad hoc networks that removes the assumption of a globally known schema and allows nodes to publish information autonomously. The model relies on the randomised dissemination and replication of metadata through a gossip protocol. Given schemas with partial similarities, the randomised metadata dissemination mechanism facilitates eventual semantic agreement and provides a substrate for the scalable discovery of content. A discovery protocol can then utilise the replicated metadata to identify content within a predictable number of hops using semantic queries. A stochastic analysis of the gossip protocol presents the different trade-offs between discoverability and replication. We evaluate the proposed model by comparing OntoMobil against a broadcast-based protocol and demonstrate that semantic discovery with proactive replication provides good scalability properties, resulting in a high discovery ratio with less overhead than a reactive non-replicated discovery approach.

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“…Each peer is characterized by a set of topics that describe its expertise. A peer knows about other peer's expertise topics by analyzing advertisement messages [12] or answers [27]. In this way, peers form clusters of semantic related expertise descriptions.…”

Section: Semantic Overlay Networkmentioning

confidence: 99%

Expertise-based peer selection in Peer-to-Peer networks

2007

Self Cite

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Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure, we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment, we show how expertise-based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages.

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Peer Selection in Peer-to-Peer Networks with Semantic Topologies

Cited by 76 publications

References 17 publications

Improving the Performance of the Peer to Peer Network by Introducing an Assortment of Methods

Improving the Performance of the Peer to Peer Network by Introducing an Assortment of Methods

Probabilistic Discovery of Semantically Diverse Content in MANETs

Expertise-based peer selection in Peer-to-Peer networks

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