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Reverse k-Nearest Neighbor Monitoring on Mobile Objects

机译:对移动对象进行反向k最近邻监视

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In this paper we focus on the problem of continuously monitoring the set of Reverse k-Nearest Neighbors (RkNNs) of a query object in a moving object database using a client server architecture. The RkNN monitoring query computes for a given query object g, the set RkNN(q) of objects having q as one of their k-nearest neighbors for each point in time. In our setting the central server can poll the exact positions of the clients if needed. However in contrast to most existing approaches for this problem we argue that in various applications, the limiting factor is not the computational time needed but the amount of traffic sent via the network. We propose an approach that minimizes the amount of communication between clients and central server by an intelligent approximation of the position of the clients. Additionally we propose several poll heuristics in order to further decrease the communication costs. In the experimental section we show the significant impact of our proposed improvements to our basic algorithm.
机译:在本文中,我们关注的问题是使用客户端服务器体系结构连续监视移动对象数据库中查询对象的反向k最近邻(RkNN)集。 RkNN监视查询为给定查询对象g计算每个时间点具有q作为其k个最近邻居之一的对象的集合RkNN(q)。在我们的设置中,如果需要,中央服务器可以轮询客户端的确切位置。但是,与大多数现有方法相比,我们认为在各种应用中,限制因素不是所需的计算时间,而是通过网络发送的流量。我们提出一种通过智能地估计客户端位置来最小化客户端与中央服务器之间的通信量的方法。另外,我们提出了几种轮询启发法,以进一步降低通信成本。在实验部分,我们展示了我们提出的对基本算法的改进的重大影响。

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