Petri-Net Based Multi-Objective Optimization in Multi-UAV Aided Large-Scale Wireless Power and Information Transfer Networks

Power consumption in wireless sensor networks is high, and the lifetime of a battery has become bottleneck, restricting network performance. Wireless power transfer with ground mobile charger vulnerable to interference from terrain other factors, hence it difficult deploy practice. Accordingly, novel paradigm adopted where multi-UAV (unmanned aerial vehicle) batteries can information SDs (sensor devices) large-scale network. However, there are discrete events, continuous process, time delay, decisions such complicated system. From perspective hybrid system, colored cyber Petri net system proposed here depict analyze this problem. Furthermore, energy utilization rate collection delay conflict each other; therefore, UAV-aided formulated as multi-objective optimization For reason, MAC-NSGA II (multiple ant colony-nondominated sorting genetic algorithm II) work. Firstly, optimal trajectory multiple UAVs was obtained, on basis, above two objectives were optimized simultaneously. Large-scale simulation results show that superior NSGA MOEA/D terms efficiency delay.