针对无线传感器网络中传统的低功耗自适应集簇分层型协议存在的节点能耗过高、网络生存周期短以及负载不均衡等问题, 本文提出了一种异构传感网络下的多目标簇头选举和基于模拟退火的哈里斯鹰路由优化算法(LEACH-MHO). 这种改进算法首先在计算节点最优阈值的基础上, 构建新的考量能耗和负载的适应度函数, 找到最优簇首节点, 保证簇首节点的均匀分布; 再建立基于哈里斯鹰优化器的路径选择策略, 同时嵌入模拟退火算法, 防止过早陷入局部最优; 最后使用评估函数筛选出可加入到最佳路径的簇头, 缩短簇头节点到基站的通信距离. 仿真实验数据表明, 与CREEP、LEACH-C、LEACH算法相比, 本文算法的网络生存寿命分别延长了22.18%、77.83%和180.52%, 能更有效地延长网络生存寿命.
Traditional low-power adaptive hierarchical cluster protocols in wireless sensor networks have high node energy consumption, short network lifetime, and unbalanced load. In order to solve these problems, this study proposes a Harris hawks routing optimization algorithm that reflects multi-objective cluster head election and is based on simulated annealing in heterogeneous sensor networks. On the basis of calculating the optimal threshold of nodes, the improved algorithm firstly constructs a new fitness function considering energy consumption and load to find the optimal cluster head node and ensure the uniform distribution of cluster head nodes. Then, a path selection strategy based on Harris hawks optimizer is established, and the simulated annealing algorithm is embedded to prevent from premature local optimum. Finally, the study uses an evaluation function to select cluster heads that can be added to the optimal path to shorten the communication distance between cluster head nodes and base stations. The simulation results show that compared with the CREEP, LEACH-C, and LEACH algorithms, the proposed algorithm prolong the network lifetime by 22.18%, 77.83%, and 180.52%, respectively, and thus they can prolong the network lifetime more effectively.