Science and Technology on Micro-System Laboratory, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 201800, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2022 Jul 29;22(15):5675. doi: 10.3390/s22155675.
As a key technology in wireless sensor networks (WSNs), target tracking plays an essential role in many applications. To improve energy efficiency, clustering is widely used in tracking to organize the network to achieve data fusion and reduce communication costs. Many existing studies make dynamic adjustments based on static clusters to track moving targets. However, the additional overhead caused by frequent cluster reconstruction and redundant data transmission is rarely considered. To address this issue, we propose a tracking-anchor-based clustering method (TACM) in this paper, in which tracking anchors are introduced to provide activation indications for sensors according to the target position. We use the rough fuzzy C-means (RFCM) algorithm to locate the anchors and use the membership table to activate sensors to form a cluster. Since there are no sending, receiving, and fusing data tasks for anchors, they are lightly burdened and can significantly reduce the frequency of being rotated. Moreover, the state of cluster members (CMs) is scheduled using the linear 0-1 programming to reduce redundant transmissions. The simulation results demonstrate that, compared with some existing clustering methods, the proposed TACM effectively reduces the energy consumption when tracking a moving target, thus prolonging the network lifetime.
作为无线传感器网络（WSN）中的一项关键技术，目标跟踪在许多应用中起着至关重要的作用。为了提高能量效率，聚类技术在跟踪中被广泛应用，用于组织网络以实现数据融合和降低通信成本。许多现有的研究基于静态聚类进行动态调整以跟踪移动目标。然而，很少考虑到频繁的簇重建和冗余数据传输所带来的额外开销。针对这一问题，我们在本文中提出了一种基于跟踪锚点的聚类方法（TACM），该方法引入跟踪锚点，根据目标位置为传感器提供激活指示。我们使用粗糙模糊 C 均值（RFCM）算法定位锚点，并使用隶属度表激活传感器以形成簇。由于锚点没有发送、接收和融合数据的任务，因此它们的负担很轻，可以显著降低旋转的频率。此外，使用线性 0-1 规划来调度簇成员（CMs）的状态，以减少冗余传输。仿真结果表明，与一些现有的聚类方法相比，所提出的 TACM 在跟踪移动目标时能有效地降低能量消耗，从而延长网络寿命。
