A Robust Unstructured Mobile Peer-to-Peer Files Sharing System under Higher Peer Churn Rate

DOI

10.2991/icsma-16.2016.42How to use a DOI?

Keywords

Mobil peer-to-peer; Churn; Files sharing; Machine learning

Abstract

In the unstructured Peer-to-Peer systems, a core operation is efficient location of resources. Conventional informative searching algorithms, however, always cannot perform well under peer churn rate network environments. In this paper, we designed a robust unstructured peer-to-peer files sharing system. When forwarding query, we usually choose the peer with the highest forward probability. But in this paper we didn't compute the forward probability according to the current neighbor node's individual search history but to a leaning model based on machine learning technologies. We proposed a more robust way for searching. The experimental results show that our methods are more effective and efficient under higher peer churn environment.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xin Zhang
AU  - Yinghu Xia
AU  - Chunqing Lin
PY  - 2016/12
DA  - 2016/12
TI  - A Robust Unstructured Mobile Peer-to-Peer Files Sharing System under Higher Peer Churn Rate
BT  - Proceedings of the 2016 4th International Conference on Sensors, Mechatronics and Automation (ICSMA 2016)
PB  - Atlantis Press
SP  - 227
EP  - 234
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsma-16.2016.42
DO  - 10.2991/icsma-16.2016.42
ID  - Zhang2016/12
ER  -