Delay Minimization for Offloaded Tasks in UAV-Assisted Mobile Edge Computing Using Ant Colony Optimization
Tanzir Ahmed, Jargis Ahmed · 2024
Mobile Edge Computing (MEC) server plays a crucial role in executing the tasks offloaded by the edge users. As MEC is deployed at the edge of the network, it helps to reduce computation latency and increase reliability for users. Due to enormous tasks offloading requests MEC may require extra resources to mitigate resource demand. In this case, MEC can deploy multiple unmanned aerial vehicles (UAVs) as computing nodes to assist with resource requirements. Now distributing the offloaded tasks and reducing the latency for task completion is a challenging problem. In this regard, we developed a delay minimization problem considering the delay and latency constraints in this paper. The formulated problem is a mixed integer problem and NP-Hard in nature. Hence we proposed an ant colony optimization (ACO) based algorithm to handle task placement in different server nodes. Extensive performance analysis indicates significant improvement in reducing delay, energy consumption of users, and success rate compared to the state-of-the-art work.