A Cross-Layer Framework for LPWAN Management based on Fuzzy Cognitive Maps with Adaptive Glowworm Swarm Optimization

In order to improve the working efficiency and reliability of energy-harvesting low-power wide area networks (EH-LPWANs) applied in smart forest monitoring, a cross-layer collaboration control model is proposed. Taking the influencing factors of EH-LPWAN as concept nodes, a fuzzy cognitive map (FCM) was devised, and the relationship between each concept was utilized to establish the cross-layer model for optimally satisfying multiple objectives and conflicting constraints. Here, a dynamic FCM scheme based on adaptive glowworm swarm optimization (AGSO) is given to determine the concept weights and sustain online updates. The results show that the energy neutrality of EH nodes and the data throughput of the entire network completely meet the real-time and stability requirements for precise forest monitoring.