基于剩余能量预测的WSN模糊分簇算法

为了进一步降低无线传感器网络的能量消耗，延长网络寿命，提出一种基于剩余能量预测的无线传感器网络模糊分簇算法。新算法根据节点到基站的距离和邻居节点的数目，对候选节点转发数据的能耗进行预估，得到节点的预测剩余能量。然后采用模糊算法在综合考虑候选节点的原始能量和预测剩余能量的基础上计算竞争半径，选出多个簇首，构建大小不均的簇。仿真实验表明，与其他路由算法相比，该算法可以更好地优化簇的结构，均衡网络能耗，延长网络的生命周期。

Fuzzy clustering hierarchy arithmetic based on residual energy prediction for WSN

In order to reduce the energy consumption and prolong the network lifetime of Wireless Sensor Networks （WSNs）, a fuzzy clustering hierarchy arithmetic based on residual energy prediction for WSNs is proposed. The new algorithm estimates required energy consumption that the candidate nodes forward their data packets to base station according to the distance between nodes and the base station and the number of neighbors, and then obtains the expected residual energy of nodes. Cluster-heads are elected on the basis of the competition radius that can be computed through fuzzy theory based on the consideration of the original energy and the remaining energy of the candidate nodes, to build clusters of uneven size. Simulation experiments show that compared with other routing algorithms, this arithmetic can better optimize the structure of the cluster, balance energy consumption, and prolong the life cycle of the network.