Approximate Aggregation for Tracking Quantiles in Wireless Sensor Networks
Approximate Aggregation for Tracking Quantiles in Wireless Sensor Networks
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DOI：
10.1007/978-3-319-12691-3_13
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发表时间：
2014-12
影响因子：
6.3
通讯作者：
Zaobo He;Zhipeng Cai;Siyao Cheng;Xiaoming Wang
中科院分区：
文献类型：
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作者：
Zaobo He;Zhipeng Cai;Siyao Cheng;Xiaoming Wang
研究了无线传感器网络中具有高效通信成本的分位数跟踪问题。与Sum、Count、Average等代数聚合相比，分位数等整体聚合能更好地表征数据分布。将到达的多组感官数据放在整个网络中，直到时间，这是节点有序收集的数据序列。目标是在有效的总通信成本和平衡的个体通信成本的情况下，持续跟踪所有接收器的近似量化。本文提出了一种基于动态二叉树的无线传感器网络跟踪近似量化的确定性跟踪算法，该算法的总通信代价为，其中为网络节点数，为数据项总数，为所需的近似误差。
We consider the problem of tracking quantiles in wireless sensor networks with efficient communication cost. Compared with the algebraic aggregations such as Sum, Count, or Average, holistic aggregations such as quantiles can better characterize data distribution. Letbe the multi-set of sensory data that have arrived until timein the entire network, which is a sequence of data orderly collected by nodes. The goal is to continuously track-approximate-quantilesofat the sink for all’s with efficient total communication cost and balanced individual communication cost. In this paper, a deterministic tracking algorithm based on a dynamic binary tree is proposed to track-approximate-quantilesin wireless sensor networks, whose total communication cost is, whereis the number of the nodes in a network,is the total number of the data items, andis the required approximation error.