Abstract
In recent years there has been a significant interest in peer-to-peer (P2P) environments in the community of data management. However, almost all works, as far, focused on exact query processing in current P2P data systems. The autonomy of peers also doesn’t be considered enough. In addition, the system cost is very high because the information publishing method of shared data is based on each document instead of document set.
In this paper, abstract indices are presented to implement content-based approximate queries in P2P data systems. It can be used to search as few peers as possible but get as many returns satisfying users’ queries as possible on the guarantee of high autonomy of peers. Also, abstract indices have low system cost, can improve the query processing speed, and support very frequent updates.
In order to verify the effectiveness of abstract indices, a simulator of 10,000 peers, over 3 million documents is made. The experimental results show that abstract indices work well in P2P data systems.
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Wang, C., Li, J., Shi, S. (2004). An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems. In: Li, M., Sun, XH., Deng, Qn., Ni, J. (eds) Grid and Cooperative Computing. GCC 2003. Lecture Notes in Computer Science, vol 3032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24679-4_69
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DOI: https://doi.org/10.1007/978-3-540-24679-4_69
Publisher Name: Springer, Berlin, Heidelberg
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