Abstract
As the amount of data is growing rapidly, efficient and scalable index structures for managing large-scale data are attracting more and more attention. To efficiently query and manage the data in metric spaces, an adaptive distributed index, MT-Chord, is proposed. MT-Chord integrates Chord based routing protocol and M-tree based index structure to support efficient similarity query processing in metric spaces. Each index node has multiple replicas for load-balance and a cost model is presented to dynamically tune the number of replicas based on the query and update pattern at the granularity of each index node. MT-Chord is a truly scalable, efficient and adaptive distributed index structure for query processing in metric spaces, which is verified by our extensive experimental studies on three real-life datasets extracted from different data sources.
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Zhu, M., Shen, D., Kou, Y., Nie, T., Yu, G. (2012). An Adaptive Distributed Index for Similarity Queries in Metric Spaces. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds) Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32281-5_22
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DOI: https://doi.org/10.1007/978-3-642-32281-5_22
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