Cloud storage system such as Amazon's Dynamo and Google's GFS poses new challenges to the community to support efficient query processing for various applications. In this paper we propose RT-HCN, a distributed indexing scheme for multi-dimensional query processing in data centers, the infrastructure to build cloud systems. RT-HCN is a two-layer indexing scheme, which integrates HCN-based routing protocol and the R-Tree based indexing technology, and is portionably distributed on every server. Based on the characteristics of HCN, we design a special index publishing rule and query processing algorithms to guarantee efficient data management for the whole network. We prove theoretically that RT-HCN is both query-efficient and space-efficient, by which each server will only maintain a tolerable number of indices while a large number of users can concurrently process queries with low routing cost. We compare our design with RT-CAN, a similar design in traditional P2P network. Experiments validate the efficiency of our proposed scheme and depict its potential implementation in data centers. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Li, F., Liang, W., Gao, X., Yao, B., & Chen, G. (2014). Efficient R-Tree based indexing for cloud storage system with dual-port servers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8645 LNCS, pp. 375–391). Springer Verlag. https://doi.org/10.1007/978-3-319-10085-2_35
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