Content discovery using people social pattern in peer-to-peer networks | |
| Author | Adhikari, Sraddha |
| Call Number | AIT Thesis no.TC-10-03 |
| Subject(s) | Peer-to-peer architecture (Computer networks) Social networks |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering inTelecommunications, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. TC-10-03 |
| Abstract | This thesis work is related toenhancing the performance of peer-to-peer (P2P) networksin terms of “ContentDiscovery”using social relationships (friendships, shared interests, shared background, experiences) between peers.Our work is highlyinfluenced by Social Networks(SN)where resources can be discovered by directly contacting some acquaintances that have informationabout the resources that we are looking for. But unfortunately, in current P2Pnetworks, the peers lack this ability and hence it is difficult to route the queries efficiently. Thus, we focus on finding a better „search technique‟ in a P2P networkby trying to exploit shared interests between peers, friendships among them and capability of memorizing experiences(encountered Queries)by them. Simply stating, the idea is tograduallydevelop social characters in lifeless P2Pnetworks and then eventually replace the terminology „peers‟ by „friends‟and node connections by relationshipsand finally build a social P2P network. Due to the fact that there is a human being behind every peer, there is similarity between social networks and P2P networks. Hence we believe and verify that human strategies in social networks are useful in improving content discoveryin P2P network. In this thesis work, we propose a “search algorithm, socP2P”which is inspired by social dynamics and behaviors.To be more precise, nodes use over-heard knowledgeand recommendationto improve search.We evaluate our approach by simulation in MATLABand comparisons with other algorithms. The simulation results show that our algorithm caneffectively identify location of requested content and solve the queries with high success rate, less delay and low overhead. We verified that our algorithm is not only useful in finding popular contents in the network but it is good enough to locate rare files as well.Results of this research demonstrate that exploiting social networks in P2P networks can make search more efficient. |
| Year | 2010 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. TC-10-03 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Telecommunications (TC) |
| Chairperson(s) | Teerapat Sanguankotchakorn |
| Examination Committee(s) | Erke, Tapio J.;Poompat Saengudomlert;Cresp, Noel;Mani, Mehdi |
| Scholarship Donor(s) | Government of Finland; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2010 |