Efficient information retrieval in mobile peer-to-peer networks

Authors:
Lijiang Chen;Bin Cui;Heng Tao Shen;Wei Lu;Xiaofang Zhou
Affiliations:
Peking University, Beijing, China;Peking University, Beijing, China;The University of Queensland, Brisbane, Australia;Renmin University of China, Beijing, China;The University of Queensland, Brisbane, Australia
Venue:
Proceedings of the 18th ACM conference on Information and knowledge management
Year:
2009

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Abstract

Mobile devices have become indispensable in daily life, and hence how to take advantage of these portable and powerful facilities to share resources and information begins to emerge as an interesting problem. In this paper, we investigate the problem of information retrieval in a mobile peer-to-peer network. The prevailing approach to information retrieval is to apply flooding methods because of its quick response and easy maintenance. Obviously, this kind of approach wastes a huge amount of communication bandwidth which greatly affects the availability of the network, and the battery power which significantly shortens the serving time of mobile devices in the network. To tackle this problem, we propose a novel approach by mimicking different human behaviors of social networks, which takes advantages of Intelligence Accuracy (IA) mechanism that evaluates the distance from a node to certain resources in the network. Extensive experimental results show the efficiency and effectiveness of our approach as well as its scalability in a volatile environment.