Cover Image

A social network Peer-to-Peer model for peer clustering

Peer clustering is a way for managing the structure of Peer-to-Peer (P2P) networks. It can be done on physical structure of the network like physical proximity of peers or semantic relationship among them. Our proposed model uses social network concepts as the main physical structure for clustering...

Full description

Saved in:
Bibliographic Details
Main Authors: Modarresi, Amir, Mamat, Ali, Ibrahim, Hamidah, Mustapha, Norwati
Format: Conference or Workshop Item
Language:English
Published: IEEE 2008
Online Access:http://psasir.upm.edu.my/id/eprint/47790/1/A%20social%20network%20Peer-to-Peer%20model%20for%20peer%20clustering.pdf
http://psasir.upm.edu.my/id/eprint/47790/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.47790
record_format eprints
spelling my.upm.eprints.477902019-05-28T07:39:13Z http://psasir.upm.edu.my/id/eprint/47790/ A social network Peer-to-Peer model for peer clustering Modarresi, Amir Mamat, Ali Ibrahim, Hamidah Mustapha, Norwati Peer clustering is a way for managing the structure of Peer-to-Peer (P2P) networks. It can be done on physical structure of the network like physical proximity of peers or semantic relationship among them. Our proposed model uses social network concepts as the main physical structure for clustering peers. Nodes in the model are grouped into several communities and sub communities with similar interests. The order and relation among communities are defined and controlled by a shared ontology. This structure provides lower distance and better locality in search. A simulation of the model shows lower path and better clustering than a random network. IEEE 2008 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/47790/1/A%20social%20network%20Peer-to-Peer%20model%20for%20peer%20clustering.pdf Modarresi, Amir and Mamat, Ali and Ibrahim, Hamidah and Mustapha, Norwati (2008) A social network Peer-to-Peer model for peer clustering. In: 3rd International Symposium on Information Technology (ITSim'08), 26-28 Aug. 2008, Kuala Lumpur, Malaysia. . 10.1109/ITSIM.2008.4631989
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Peer clustering is a way for managing the structure of Peer-to-Peer (P2P) networks. It can be done on physical structure of the network like physical proximity of peers or semantic relationship among them. Our proposed model uses social network concepts as the main physical structure for clustering peers. Nodes in the model are grouped into several communities and sub communities with similar interests. The order and relation among communities are defined and controlled by a shared ontology. This structure provides lower distance and better locality in search. A simulation of the model shows lower path and better clustering than a random network.
format Conference or Workshop Item
author Modarresi, Amir
Mamat, Ali
Ibrahim, Hamidah
Mustapha, Norwati
spellingShingle Modarresi, Amir
Mamat, Ali
Ibrahim, Hamidah
Mustapha, Norwati
A social network Peer-to-Peer model for peer clustering
author_facet Modarresi, Amir
Mamat, Ali
Ibrahim, Hamidah
Mustapha, Norwati
author_sort Modarresi, Amir
title A social network Peer-to-Peer model for peer clustering
title_short A social network Peer-to-Peer model for peer clustering
title_full A social network Peer-to-Peer model for peer clustering
title_fullStr A social network Peer-to-Peer model for peer clustering
title_full_unstemmed A social network Peer-to-Peer model for peer clustering
title_sort social network peer-to-peer model for peer clustering
publisher IEEE
publishDate 2008
url http://psasir.upm.edu.my/id/eprint/47790/1/A%20social%20network%20Peer-to-Peer%20model%20for%20peer%20clustering.pdf
http://psasir.upm.edu.my/id/eprint/47790/
_version_ 1643833983360827392
score 13.211869

Similar Items