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An Improved Dynamic Coalition Generation Based on Ant Colony Algorithm for Target Detection in Wireless Sensor Network

机译:改进的基于蚁群算法的动态联盟生成在无线传感器网络中的目标检测

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The cooperation among sensor nodes is a significant issue in large-scale, complicated Wireless Sensor Networks(WSN). Target tracking is a canonical application of WSN. The dynamic coalition mechanism in WSN for target detection is an important method to improve the tracking quality which saves much energy. An energy efficient coalition formation algorithm is needed because the energy resource of WSN is restricted. In this paper, we propose a WSN dynamic coalition formation based on Ant Colony algorithm (DCF_AC). The sink node of every group is the group head, which knows the global coordinate of its own and inclines to wake sensor nodes around the target with high residual energy to form coalition periodically. The algorithm can balance the energy consumption among sensor nodes, so as to extend the network lifetime for more tasks. The results of experiments concludes the validity of this algorithm.
机译:在大规模,复杂的无线传感器网络(WSN)中,传感器节点之间的协作是一个重要的问题。目标跟踪是WSN的规范应用。 WSN中用于目标检测的动态联盟机制是提高跟踪质量,节省大量能量的重要方法。由于限制了WSN的能源,因此需要一种高效的联盟形成算法。在本文中,我们提出了一种基于蚁群算法(DCF_AC)的WSN动态联盟结构。每个组的汇点节点都是组头,组头知道其自身的全局坐标,并倾向于以较高的剩余能量唤醒目标周围的传感器节点,从而周期性地形成联盟。该算法可以平衡传感器节点之间的能耗,从而延长网络寿命以应对更多任务。实验结果证明了该算法的有效性。

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