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An efficient index structure for distributed k -nearest neighbours query processing
Soft Computing ( IF 2.784 ) Pub Date : 2018-09-26 , DOI: 10.1007/s00500-018-3548-4
Min Yang, Kun Ma, Xiaohui Yu

Abstract Many location-based services are supported by the moving k-nearest neighbour (k-NN) query, which continuously returns the k-nearest data objects for a query point. Most of existing approaches to this problem have focused on a centralized setting, which show poor scalability to work around massive-scale and distributed data sets. In this paper, we propose an efficient distributed solution for k-NN query over moving objects to tackle the increasingly large scale of data. This approach includes a new grid-based index called Block Grid Index (BGI), and a distributed k-NN query algorithm based on BGI. There are three advantages of our approach: (1) BGI can be easily constructed and maintained in a distributed setting; (2) the algorithm is able to return the results set in only two iterations. (3) the efficiency of k-NN query is improved. The efficiency of our solution is verified by extensive experiments with millions of nodes.
更新日期:2020-03-24

 

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