利用簇收缩策略的传感器节点重要性评估算法

针对现有借助移除思想设计的节点重要性评估方法不能准确刻画网络中传感器节点重要性的问题,提出了一种新颖的传感器节点重要性评估算法.该算法利用簇收缩策略来代替传感器节点的移除,进而有效规避了由节点移除而引发的网络拓扑不稳定及断裂等现象.具体步骤是首先凭借谱分析方法找出网络中的原始簇结构,然后借助簇收缩策略找出网络中的重要节点,最后利用超能节点来实现对重要节点的针对性保护,进而达到延长无线传感器网络寿命和增强网络抗毁性的目标.相关仿真也验证了所提算法的有效性.

Novel sensor node importance evaluation method based on the agglomeration contraction principle

Node importance evaluation based on removal of nodes and their incident links cannot accurately reflect the importance of the nodes. Because this way may change the topology of wireless sensor networks, and even splits the network into several disconnected parts. To solve this question, we propose a novel node importance evaluation method based on the agglomeration contraction principle. This method does not need to remove the assessment node from the network, and thus this method may not cause the network to be fractured. In this method, with the help of a spectral method, the vital gateway nodes can be obtained by using the nontrivial eigenvectors of the Laplace matrix of the network diagram firstly. After that, by using some super-energy nodes to provide targeted protection for vital gateway nodes in a wireless sensor network, this way can prolong the life of the network and improve the robustness of the system effectively. Above all, this method can reduce the number of evaluation nodes in a wireless sensor network, and decrease the workload of calculation accordingly. Final examples verify its efficiency and the result is consistent with our intuitive judgments.