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Controlled Mobility Sensor Networks for Target Tracking Using Ant Colony Optimization

机译:使用蚁群优化进行目标跟踪的可控运动传感器网络

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In mobile sensor networks, it is important to manage the mobility of the nodes in order to improve the performances of the network. This paper addresses the problem of single target tracking in controlled mobility sensor networks. The proposed method consists of estimating the current position of a single target. Estimated positions are then used to predict the following location of the target. Once an area of interest is defined, the proposed approach consists of moving the mobile nodes in order to cover it in an optimal way. It thus defines a strategy for choosing the set of new sensors locations. Each node is then assigned one position within the set in the way to minimize the total traveled distance by the nodes. While the estimation and the prediction phases are performed using the interval theory, relocating nodes employs the ant colony optimization algorithm. Simulations results corroborate the efficiency of the proposed method compared to the target tracking methods considered for networks with static nodes.
机译:在移动传感器网络中,重要的是管理节点的移动性,以提高网络的性能。本文解决了受控运动传感器网络中的单个目标跟踪问题。所提出的方法包括估计单个目标的当前位置。然后,将估计的位置用于预测目标的后续位置。一旦定义了感兴趣的区域,建议的方法就是移动移动节点,以便以最佳方式覆盖它。因此,它定义了用于选择一组新传感器位置的策略。然后,以最小化节点的总行进距离的方式,将每个节点分配给集合中的一个位置。在使用间隔理论执行估计和预测阶段的同时,重定位节点采用蚁群优化算法。与针对具有静态节点的网络考虑的目标跟踪方法相比,仿真结果证实了该方法的效率。

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