An Energy Efficient Offloading Technique for UAV-Assisted MEC Using Nature Inspired Algorithm

The significance of unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC)-based applications is increasing exponentially with the prolification of technological advancement. UAV-assisted MEC-based applications need real-time responses during offloading. With the aim to minimize the overall execution time during offloading, the energy issue got compromised. Although, energy issue of UAV-assisted MEC is a very important performance factor. Here, an energy efficient full offloading technique for UAV-assisted mobile edge servers (EEFOUM) is proposed. The design EEFOUM is explored with an renowned evloutionary algorithm, namely as particle swarm optimization (PSO). The PSO-based EEFOUM algorithm computes the overall energy consumption with the deployment of fixed-wing UAVs and rotary-wing UAVs.