BRTCO: A Novel Boundary Recognition and Tracking Algorithm for Continuous Objects in Wireless Sensor Networks
BRTCO: A Novel Boundary Recognition and Tracking Algorithm for Continuous Objects in Wireless Sensor Networks
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BRTCO：无线传感器网络中连续物体的新型边界识别和跟踪算法
DOI：
10.1109/jsyst.2016.2593949
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发表时间：
2018-09-01
影响因子：
4.4
通讯作者：
Shu, Lei
中科院分区：
文献类型：
--
作者：
Han, Guangjie;Shen, Jiawei;Shu, Lei
连续目标监测和跟踪是无线传感器网络最突出的应用之一，其目的是检测未经授权的感兴趣的材料的入侵。在本文中，我们提出了一种新的边界识别和跟踪算法的连续对象（BRTCO），以确保目标轮廓提取的效率。在保证跟踪精度的前提下，提出了一种最小化边界节点数的协同过滤算法。同时，在数据传输阶段，我们利用分簇的优势，以确保能源效率。设计了一种基于簇头竞争的报告节点选择机制。仿真结果表明，BRTCO可以显着降低总能耗，边界节点的数量，报告节点的数量。
Continuous objects monitoring and tracking, which aims to detect the invasion of unauthorized materials of interest, is one of the most prominent applications in wireless sensor networks. In this paper, we propose a novel boundary recognition and tracking algorithm for continuous objects (BRTCO) to ensure the efficiency of objects contour extraction. On precondition of assuring the tracking accuracy, a collaborative filtering scheme is proposed to minimize the number of boundary nodes. Also, in the phase of data transmission, we take the advantage of clustering to ensure energy efficiency. A report node selection mechanism is designed based on the competition of cluster heads. Simulation results demonstrate that BRTCO can significantly reduce the total energy consumption, the number of boundary nodes, and the number of report nodes.