无线传感器网络（Wireless Sensor Network，WSN）是一种新型无线智能网络，具有自组织能力强，可随机部署特点，广泛应用在环境监测、医疗、智能家居等领域。但组成WSN的众多传感器节点采用一次性电池供能，节点能量耗尽并不能及时充电，影响WSN正常运行。在资源有限情况下，设计高效节能路由算法寻找“高效”路径，降低网络能耗具有十分重要的研究意义和价值。本文通过对经典分簇路由算法的研究和改进，以节能高效路由为目标，提出基于分区和优化阈值函数的改进LEACH算法和基于遗传算法的分簇路由算法，研究内容如下：

针对LEACH路由存在簇头随机选举，簇间单跳路由传输造成簇头耗能加快等问题，提出一种基于分区和阈值优化的改进LEACH算法。该算法考虑节点剩余能量、邻居节点数及节点距基站距离三因素对簇头选举函数进行优化，同时对WSN部署区域进行划分，不同分区采取不同数据传输方式，降低基站附近簇头节点转发负载。结果表明，与LEACH、LEACH-EDP相比，第一死亡节点运行时间分别延长了41.22%、14.94%，在提高网络稳定性方面有更好的性能表现。

在改进的LEACH算法基础上，对于循环成簇会造成节点通信能耗加剧问题，提出一种基于遗传算法的分簇路由算法。利用遗传算法设计一种动态的簇头选举方法，在稳定阶段引入代价函数，改进簇间下一跳转发节点的选择策略，选择能量充足、位置更优的簇头进行数据转发。仿真结果表明，该算法相比LEACH、LEACH-EDP和改进的LEACH，能够降低节点无线通信能耗，提高节点能量利用率，延长网络的生命周期，同时该算法在大区域下也有良好的性能表现。

Wireless Sensor Network (Wireless Sensor Network, WSN) is a new type of wireless intelligent network with strong self-organization ability and random deployment characteristics. It is widely used in environmental monitoring, medical treatment, smart home and other fields. However, the sensor node uses disposable batteries for energy, and the node energy is exhausted and cannot be charged in time, which affects the normal operation of the WSN. In the case of limited resources, designing high-efficiency and energy-saving routing algorithms to find "efficient" paths and reducing network energy consumption has important research significance and value. Based on the research and improvement of the classic cluster routing algorithm, this paper proposes an improved LEACH algorithm based on partitioning and optimized threshold function and a cluster routing algorithm based on genetic algorithm with the goal of energy-saving and efficient routing. The research content is as follows:

Aiming at the problems of LEACH routing with random election of cluster heads, and accelerating energy consumption of cluster heads caused by single-hop routing between clusters, an improved LEACH algorithm based on partition and threshold optimization is proposed. The algorithm considers the remaining energy of nodes, the number of neighbor nodes and the distance from the base station to optimize the cluster head election function. At the same time, the WSN deployment area is divided. Different partitions adopt different data transmission methods to reduce the forwarding load of cluster head nodes near the base station. The results show that compared with LEACH and LEACH-EDP, the running time of the first dead node is extended by 41.22% and 14.94%, respectively, and it has better performance in improving network stability.

On the basis of the improved LEACH, a clustering routing algorithm based on genetic algorithm is proposed to solve the problem that the cyclic clustering will increase the energy consumption of node communication. A dynamic cluster head election method is designed using genetic algorithm, a cost function is introduced in the stable phase, the selection strategy of the next hop sending node between clusters is improved, and the cluster head with sufficient energy and better location is selected for data forwarding. Simulation results show that compared with LEACH, LEACH-EDP and improved LEACH, the algorithm can reduce the energy consumption of node wireless communication, improve node energy utilization, and extend the life cycle of the network. At the same time, the algorithm also has good performance in large areas.

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