Task migration method based on load balancing in mobile edge computing

The invention belongs to the technical field of mobile communication, and particularly relates to a task migration method based on load balancing in mobile edge computing. The method comprises the following steps: constructing a multi-user multi-node mobile edge computing system model; constructing a communication model, a task calculation model, a user QoS model and a load balancing model based on the mobile edge computing system model; constructing an optimization problem for maximizing the QoS of the minimum user; a multi-agent deep reinforcement learning algorithm is adopted to solve the optimization problem of maximizing the minimum user QoS, and an unloading decision, a migration decision and a power distribution decision of a task are obtained; the system carries out task migration according to an unloading decision, a migration decision and a power distribution decision of the task; according to the method, the task execution time delay, the task failure rate and the migration rate can be effectively