Multi-edge Server Load Balancing Offloading Method Based On Ant Colony Algorithm

The deployment of multiple edge servers has a significant difference in the performance of mobile edge computing(MEC) due to the more diverse options for computing offloading. This paper proposes an Ant Colony Multi-edge Load-balancing Offloading (ACMLO) strategy based on ant colony algorithm. Under the premise of considering the existing load of each edge server, the problem is modeled as a general multi-constraint optimization problem, and the optimization goal is to minimize the weighted sum of energy consumption and delay. Then use the general constraint form of slack variable method and exponential method (PHR algorithm) to solve iteratively. In each iteration, the ant colony algorithm is used to make decisions on the division of subtasks and the allocation of channel bandwidth, so as to achieve load balancing. The simulation results show that the proposed strategy can effectively improve the computational offload performance and meet the differentiated needs of users.