基于时空加权目标函数的无线传感网分簇协议

针对无线传感器网络中能量受限的特点，提出了基于时空相关加权目标函数粒子群优化算法（SC-WOFPSO）的分簇协议。首先，该协议使用Kohonen神经网络提取节点间的数据相似性。在分簇过程中，该协议综合考虑了节点间的数据相似性、节点间距离以及节点剩余能量等因素，使用PSO算法进行迭代寻优，寻找最优的簇头集合；在成簇过程中，网络中的非簇头节点为每个簇头分别计算goal函数值，选择加入函数值最大的簇头。最后从网络总能量消耗、网络寿命和网络吞吐量三个性能指标出发，验证了该协议能够有效降低网络能耗、提高网络寿命、提高网络吞吐量。

Clustering protocol for wireless sensor network based on spatio-temporal weighted objective function

According to the characteristics of energy limitation in wireless sensor networks, this paper proposed a clustering protocol based on spatiotemporal correlation weighted objective function particle swarm optimization algorithm(SC-WOFPSO). Firstly, this protocol used Kohonen neural network to extract the data similarity between nodes. In the process of clustering, this protocol comprehensively considered the data similarity between nodes, the distance between nodes and the residual energy of cluster head nodes, and used PSO algorithm for iterative optimization to find the optimal cluster head set. In the process of cluster, the non cluster head nodes in the network calculated the goal function value for each cluster head, and chose to join the cluster head with the maximum function value. Finally, this paper started from the three performance indicators of total network energy consumption, network life and network throughput to verify the protocol. The result shows that this protocol can effectively reduce network energy consumption, increase network life and network throughput.