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.

中文翻译：

---

分布式k最近邻查询处理的有效索引结构

摘要

移动的k最近邻居（k -NN）查询支持许多基于位置的服务，该查询连续返回查询点的k最近数据对象。解决此问题的大多数现有方法都集中在集中式设置上，这表明在大规模和分布式数据集上工作时可伸缩性较差。在本文中，我们提出了一种有效的分布式解决方案，用于在运动对象上进行k -NN查询，以解决日益庞大的数据量。这种方法包括一个新的基于网格的索引，称为块网格索引（BGI），以及一个分布式k基于BGI的-NN查询算法。我们的方法具有三个优点：（1）BGI可以轻松地构建和维护在分布式环境中；（2）该算法仅能在两次迭代中返回结果集。（3）提高了k -NN查询的效率。我们的解决方案的效率通过数百万个节点的广泛实验得到了验证。