【摘要】 针对部署在列车的长带状无线传感器网络(WSNs)产生的能耗不均问题，提出了一种基于改进蚁群优化的列车WSNs非均匀分簇路由算法(IACO-UCR)。在非均匀分簇阶段，利用熵权法对候选簇首的传输距离、中心位置度和相对密度各项指标进行权重确定，在综合评价确定候选簇首时引入能量优先的概念，候选簇首以其竞争半径成为最终簇首；然后将改进的蚁群优化算法应用到簇间路径搜索中，在建立路径过程中考虑到距离长度、节点能量和搜索方向角度等因素。由MATLAB仿真实验表明：与LEACH,EEUC和ACOUC算法相比，该算法能有效均衡长带状网络的能量问题，提高簇首节点能量利用率，延长了网络的生存周期。更多还原

【Abstract】 Aiming at the uneven energy consumption caused by the long-strip wireless sensor networks(WSNs)deployed on the train, an improved ant colony optimization algorithm based uneven clustering routing algorithm(IACO-UCR)for train WSNs is proposed.In the non-uniform clustering stage, the entropy weight method is used to weight the transmission distance, center position and relative density of the candidate cluster heads.The concept of energy priority is introduced when the candidate cluster heads are determined in a comprehensive evaluation.The competition radius becomes the final cluster head; then the improved ant colony optimization algorithm is applied to the path search between clusters, and factors such as distance length, node energy and search direction angle are considered in the process of establishing the path.From the MATLAB simulation experiment, it can be known that compared with LEACH,EEUC and ACOUC algorithms, this algorithm can effectively balance the energy problem of long strip networks, improve the energy utilization of cluster head nodes, and extend the life cycle of the network.更多还原