A Node Placement Optimization Algorithm in Heterogeneous WSN Based on Neighbor Nodes

Wireless sensor network (WSN) is an important part of the Internet of Things. With the application and development of the Internet of Things, the heterogeneity of WSN is put forward a higher demand. Node placement is a critical step in the heterogeneous wireless sensor network (HEWSN). It is very important to optimize the node placement to fundamentally prolong the lifetime, improve the performance, and decrease the cost of the HEWSN. In this paper, the node placement optimization problem of HEWSN with different sensing types’ nodes is studied. An improved algorithm named neighbor nodes directed evolved nondominated sorting genetic algorithm (NN-DENSGA) is proposed to solve the multiobjective optimization problem. Homogeneous neighbor nodes are considered to promote directional evolution, and heterogeneous neighbor nodes are considered to repair the coverage holes. In addition, a forced update strategy is designed to increase diversity of population. Experiments have shown that the proposed algorithm not only has improvements in optimization performance but also in convergence speed and stability.