Multi Task Multi-UAV Computation Offloading Enabled Mobile Edge Computing Systems

Mobile edge computing (MEC) is a technology that has found effective solutions in terms of ultra-low latency, low energy consumption, high data rate and high reliability. MEC is become actual appropriate for the devices that has a limited resource such IoT, UAVs etc. In this paper, we consider an algorithm to improve and minimize the energy consumption of Unmanned Aerial Vehicle by offloading and execution some tasks of UAV into nearby UAVs or into edge cloud server. The proposed algorithm is based on dynamic programming that uses a randomization and hamming distance termination to obtain approximately optimal solution. The algorithm can minimize the energy consumption of UAV and improving the total execution time by offload some tasks to nearby UAVs or to edge cloud server when transmission data rate of the network is high. The algorithm can find a nearly optimal offloading decision within a few repetitions. The results show that the proposed algorithm achieves a minimal energy while meeting energy and time constraints.