Itinerary planning in wireless sensor networks using fuzzy logic and particle swarm optimization

Abstract Wireless sensor networks (WSNs) can benefit from mobile agent technology in several ways, including decreased network traffic and energy-efficient data collection techniques. Path scheduling for mobile agents (MAs) is currently a crucial component of WSNs. However, routing all MAs across WSNs must be carefully organized to reduce resource costs and increase information accuracy. Numerous studies have developed routing algorithms for installing several MAs in a particular network. They planned routes, so the mobile agent checks pursued distinct paths to gather information from the nodes efficiently. This paper presents a novel fuzzy logic-based particle swarm optimization itinerary planning technique (FLPSO). The FLPSO employs techniques associated with the fuzzy logic model (FLM) and classifies the sensor into distinct types depending on the paths specified by the mobile agent trips. Mobile agents adhere to hybrid planning determined by particle swarm optimization (PSO) planning and gather data only from authorized groups. The experimental results illustrate the efficacy and superiority of the proposed method over current methods, concerning 10% better energy consumption and 15% better task delay (time).