Improving peer-to-peer search performance through intelligent social search

Yang, Stephen J. H.; Zhang, Jia; Lin, Chung-Cherng; Tsai, Jeffrey J. P.

doi:10.1016/j.eswa.2009.01.045

Cited by 13 publications

(7 citation statements)

References 39 publications

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“…By targeting these high degree peers during a search, we could decrease search time and increase breadth of search and diversity of results. This is particularly applicable to works such as [5], [21] and [22], where social search can be enhanced by estimating the peer degree centrality in the projection graph.…”

Section: Summary and Discussionmentioning

confidence: 99%

“…In other works such as [21], peers are organized into social P2P networks based on similar preferences, interests or knowledge of their users, to improve search by utilizing peers trusted or relevant to the search. Similarly, in [22] a socialbased overlay for unstructured P2P networks is outlined, that enables peers to find and establish ties with other peers if their owners have common interest in specific types of content, thus improving search and reducing overlay construction overhead.…”

Section: Related Workmentioning

confidence: 99%

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Inferring peer centrality in socially-informed peer-to-peer systems

Kourtellis

Iamnitchi

2011

2011 IEEE International Conference on Peer-to-Peer Computing

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Social applications implemented on a peer-to-peer (P2P) architecture mine the social graph of their users for improved performance in search, recommendations, resource sharing and others. In such applications, the social graph that connects their users is distributed on the peer-to-peer system: the traversal of the social graph translates to a socially-informed routing in the peer-to-peer layer.In this work we introduce the model of a projection graph that is the result of mapping a social graph onto a peer-to-peer network. We analytically formulate the relation between metrics in the social graph and in the projection graph. We focus on three such graph metrics: degree centrality, node betweenness centrality, and edge betweenness centrality. We evaluate experimentally the feasibility of estimating these metrics in the projection graph from the metrics of the social graph. Our experiments on real networks show that when mapping communities of 50-150 users on a peer, there is an optimal organization of the projection graph with respect to degree and node betweenness centrality. In this range, the association between the properties of the social graph and the projection graph is the highest, and thus the properties of the (dynamic) projection graph can be inferred from the properties of the (slower changing) social graph. We discuss the applicability of our findings to aspects of peer-to-peer systems such as data dissemination, social search, peer vulnerability, and data placement and caching.

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Section: Summary and Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Inferring peer centrality in socially-informed peer-to-peer systems

Kourtellis

Iamnitchi

2011

2011 IEEE International Conference on Peer-to-Peer Computing

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“…Authors in [32] present theoretical findings explaining the property that a specific person can be reached via a small number of hops in a peer-to-peer social network. In [33], it is pointed out how intelligent social search shortens search routes and improves peer-to-peer search performance. SPROUT [34] is a peer-to-peer routing algorithm that uses social links to increase the number of query results and reduce query delays.…”

Section: Related Workmentioning

confidence: 99%

P2Care: A dynamic peer-to-peer network for collaboration in personalized healthcare service delivery

Andriopoulou

Birkos

Lymberopoulos

2015

Computers in Industry

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“…First, there are direct consequences for the performance of social applications mining a SG distributed on a P2P system. For example, social search [5], [19] is a method of connecting users to context-relevant content made available by their friends. A social search query follows contextually relevant SG edges over multiple social hops.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Peer Centrality in the Designof Socially-Informed Peer-to-Peer Systems

Kourtellis

Iamnitchi

2014

IEEE Trans. Parallel Distrib. Syst.

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Social applications mine user social graphs to improve performance in search, provide recommendations, allow resource sharing and increase data privacy. When such applications are implemented on a peer-to-peer (P2P) architecture, the social graph is distributed on the P2P system: the traversal of the social graph translates into a socially-informed routing in the peer-to-peer layer. In this work we introduce the model of a projection graph that is the result of decentralizing a social graph onto a peer-to-peer network. We focus on three social network metrics: degree, node betweenness and edge betweenness centrality and analytically formulate the relation between metrics in the social graph and in the projection graph. Through experimental evaluation on real networks, we demonstrate that when mapping user communities of sizes up to 50-150 users on each peer, the association between the properties of the social graph and the projection graph is high, and thus the properties of the (dynamic) projection graph can be inferred from the properties of the (slower changing) social graph. Furthermore, we demonstrate with two application scenarios on large-scale social networks the usability of the projection graph in designing social search applications and unstructured P2P overlays. !• Nicolas Kourtellis and Adriana Iamnitchi are with the and anda@cse.usf.edu. social network providers and better service availability for social services mining the SG than mobile devices. Given such P2P solutions, the present work addresses the following question: How does the SG topology and its decentralization affect the network properties of peers and the routing in the P2P system?

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Improving peer-to-peer search performance through intelligent social search

Cited by 13 publications

References 39 publications

Inferring peer centrality in socially-informed peer-to-peer systems

Inferring peer centrality in socially-informed peer-to-peer systems

P2Care: A dynamic peer-to-peer network for collaboration in personalized healthcare service delivery

Leveraging Peer Centrality in the Designof Socially-Informed Peer-to-Peer Systems

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