Distributed Grid-Based K Nearest Neighbour Query Processing Over Moving Objects
K-nearest neighbour (k-NN) queries over moving objects is a classic problem with applications to a wide spectrum of location-based services. Abundant algorithms exist for solving this problem in a centralized setting using a single server, but many of them become inapplicable when distributed processing is called for tackling the increasingly large scale of data. To address this challenge, we propose a distributed grid-based solution to k-NN query processing over moving objects. First, we design a new grid-based index called Block Grid Index (BGI), which indexes moving objects using a two-layer structure and can be easily constructed and maintained in a distributed setting. We then propose a distributed k-NN algorithm based on BGI, called DBGKNN. We implement BGI and DBGKNN in the commonly used master-worker mode, and the efficiency of our solution is verified by extensive experiments with millions of nodes.
KeywordsQuery Processing Query Time Baseline Method Query Object Split Operation
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- 1.Chaudhuri, S., Gravano, L.: Evaluating top-k selection queries. In: VLDB, vol. 99, pp. 397–410 (1999)Google Scholar
- 4.Roussopoulos, N., Kelley, S., Vincent, F.: Nearest neighbor queries. In: ACM Sigmod Record, vol. 24, pp. 71–79. ACM (1995)Google Scholar
- 5.Seidl, T., Kriegel, H.-P.: Optimal multi-step k-nearest neighbor search. In: ACM SIGMOD Record, vol. 27, pp. 154–165. ACM (1998)Google Scholar
- 6.Šidlauskas, D., Šaltenis, S., Jensen, C.S.: Parallel main-memory indexing for moving-object query and update workloads. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 37–48. ACM (2012)Google Scholar
- 8.Tao, Y., Papadias, D., Shen, Q.: Continuous nearest neighbor search. In: Proceedings of the 28th International Conference on Very Large Data Bases, pp. 287–298. VLDB Endowment (2002)Google Scholar
- 9.Yu, C., Ooi, B.C., Tan, K.-L., Jagadish, H.: Indexing the distance: an efficient method to knn processing. In: VLDB, vol. 1, pp. 421–430 (2001)Google Scholar
- 10.Yu, X., Pu, K.Q., Koudas, N.: Monitoring k-nearest neighbor queries over moving objects. In: Proceedings of 21st International Conference on Data Engineering, ICDE 2005, pp. 631–642. IEEE (2005)Google Scholar