Hierarchical type-II fuzzy logic routing scheme enabled with PSO algorithm in flying ad hoc networks

Abstract

Flying ad hoc networks—composed of self-organizing unmanned aerial vehicles (UAVs)—offer numerous applications in various fields, including military operations, industry, and agriculture. Due to the UAV network's unique characteristics, such as high node velocity, sparse UAV distributions, and frequent topology changes, their data routing encounters significant challenges, compromising the quality of service aspects. We introduce a hierarchical type-II fuzzy logic system integrated with a particle swarm optimization algorithm aimed at enhancing the quality of service parameters. The UAVs’ link quality, residual energy, distance, neighboring nodes’ degree, movement direction, and relative velocity are the fuzzy system inputs to compute UAV nodes’ utility, forming the most suitable multiple relay nodes in the optimized link state routing protocol. Meanwhile, our approach employs a hierarchical fuzzy structure to address the curse of dimensionality caused by the exponential growth of fuzzy rules. Furthermore, the particle swarm optimization algorithm adjusts the fuzzy membership functions to tackle ambiguity and uncertainty in the UAV environment. We simulate our approach using NS-3 and compare it with traditional methods under varying node densities and mobility models. The simulation outcomes demonstrate that our approach enhances end-to-end delay, packet delivery ratio, network throughput, and energy consumption compared to rival schemes.