基于自适应动态簇和预测机制的WSN目标跟踪算法

Target Tracking Based on Adaptive Dynamic Clusters and Prediction Mechanism in WSN

无线传感器网络由大量能量有限的传感器节点组成,如何高效利用网络中节点的能量是无线传感器网络用于目标跟踪时研究的主要内容。合理构建动态簇可以有效降低网络的能量消耗,延长网络的生命周期,本文通过改进动态簇组建过程中簇头的选举和簇成员的征集过程,达到进一步节能的效果。其中,簇头的选择,综合考虑节点的能量和节点离目标的距离两个因素。簇成员的征集,同时考虑目标的移动速度和网络中节点的分布情况。同时,引入有效的预测机制,通过避免盲目的唤醒网络中的节点和降低跟踪延迟,可以进一步增强网络的跟踪性能,使跟踪过程更加有效和稳定。仿真结果表明本文算法在保证跟踪精度的前提条件下,可以有效节省网络中节点的能量。

Wireless sensor network is composed of a lot of energy limited sensor nodes,therefore,how to use the en-ergy of nodes in network efficiently is one of the major challenges for target tracking in sensor network. It proves thereasonable construction of dynamic cluster structure can not only reduce the network energy consumption effective-ly but also reinforce the lifecycle of the network. By improving methods of the choose of cluster heads and the selec-tion of the cluster members in the process of dynamic cluster construction,this paper is aimed to achieve the fur-ther effect of energy saving. The choose of cluster heads is based on the energy of the nodes and the distance fromnode to target. The selection of the cluster members takes the target＇s movement speed and the distribution of net-work nodes into consideration. And the introduction of effective prediction mechanism which can avoid waking upnodes in the network blindly and reduce the time delay of tracking process can further enhance the tracking perfor-mance of the network. In addition,the effective prediction mechanism makes the tracking process more effectiveand stable. The simulations show that the algorithm in this paper can save the energy of the nodes in the network ef-fectively under the tracking precision condition.