A community-based peer-to-peer model based on social networks
Improving search performance is an important issue in peer-to-peer (P2P) network systems. The structure of underlying models has a direct effect on the performance of the search algorithms. In unstructured system like Gnutella query flooding algorithm suffers from poor scalability and considera...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/12661/1/A%20community.pdf |
| Summary: | Improving search performance is an important issue in
peer-to-peer (P2P) network systems. The structure of
underlying models has a direct effect on the performance
of the search algorithms. In unstructured system like
Gnutella query flooding algorithm suffers from poor
scalability and considerable network overhead. In
structured systems, algorithms like CAN and CHORD
provide better performance, but they need more
administrative tasks and have limited functionality in
search. Our proposed model is a semi-structured, based
on social networks which uses flooding algorithm for
searching. Nodes in the model are grouped into several
communities and sub communities with similar interests
which provide lower distance and better locality in
search. A simulation of the model shows lower path and
better clustering than a random network. |
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