Abstract
So far, query routing strategies of unstructured P2P system are described qualitatively or conducted expensively. In this paper, we propose an adaptive query routing method by using quantitative information in the form of probabilistic knowledge for the purpose of (1) maximizing the likelihood of locating desired resource, and (2) using feedback from previous user queries to update the probabilistic information for guiding future ones. To achieve the goal, two kinds of probabilistic information are considered: information about overlap between topics and coverage and completeness of each peer. A declarative formalism for specifying the two kinds of probabilistic information is described, and then the algorithms for using and maintaining such information are presented. Finally, a preliminary experiment is conducted to evaluate the efficiency and effectiveness of our proposed approach.
This work was supported by National Natural Science Foundation of China under grant No. 60373019, and by Science and Technology Commission of Shanghai Municipal Government under grant No. 03DZ15028.
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Xu, L., Dai, C., Cai, W., Zhou, S., Zhou, A. (2004). Towards Adaptive Probabilistic Search in Unstructured P2P Systems. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds) Advanced Web Technologies and Applications. APWeb 2004. Lecture Notes in Computer Science, vol 3007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24655-8_28
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DOI: https://doi.org/10.1007/978-3-540-24655-8_28
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