Research on Collaborative Computational Offload Strategy Based on Improved Ant Colony Algorithm in Edge Computing

With the development of intelligent terminals and telecommunications technology, many new applications such as driverless driving,Internet of things continues to emerge, in order to meet the user's low-latency response needs, mobile edge computing (MEC) came into being. At present, mobile edge computing mainly studies how to reduce the latency and energy consumption of users, when processing tasks, in the face of some dense tasks, the ECS processing delay is too long, but the local edge server has a lot of idleness. In order to reduce latency and energy consumption, this paper proposes an edge cloud collaborative offload strategy based on improved ant colony algorithm (IACO). The final simulation results are compared with the random unloading algorithm, the local unloading algorithm and the traditional ant colony algorithm algorithm, and the improved ant colony algorithm is the effect is the best.