LEACH Protocol Analysis and Optimization of Wireless Sensor Networks Based on PSO and AC

Nowadays, wireless sensor networks (WSN) technology has become a research hotspot for information gathering in the Internet of Things. In view of the limited energy of WSN and the large amount of data transmission, it is essentially important to optimize LEACH protocol for network data transmission of WSN. This paper uses ant colony algorithm (AC) and particle swarm algorithm (PSO) to optimize the LEACH protocol most commonly used in WSN routing protocol, in order to reduce the energy consumption of WSN data transmission and optimize the data transmission routing. In the clustering process of LEACH protocol, the cluster heads are randomly chosen without considering the energy consumption caused by factors such as location and data analysis, resulting in that the selected cluster heads are not the optimal one. Therefore, PSO is used to optimize LEACH protocol so as to get the most global optimal communication representative-cluster head. In the data transmission phase of LEACH protocol, a single-hop route is easy to cause a cluster head to consume all the energy too earlier, thus the network cycle is shortened. In order to solve this problem, the inter-cluster communication route is established with the help of the AC, turning the single-hop route to multi-hop route algorithm. Considering that the AC algorithm is prone to fall into a local optimal solution, PSO is used to interfere with the updated pheromone to get rid of the local optimal solution thus accelerating its acquisition of the global optimal communication path under the LEACH protocol. The simulation results show the performance of artificial intelligence (AI) of LEACH routing protocol is enhanced and its imbalance between the data transmission and network energy consumption is well solved through jointly integrated innovation method of AI algorithm.