Task Allocation Method for Power Internet of Things Based on Two-Point Cooperation

Edge computing calculates computing tasks on computing resources close to the data source, which can effectively reduce the latency of the computing system, reduce data transmission bandwidth, and ease the pressure on the cloud computing center. However, with the explosive growth of business terminals, the capacity of a single edge node is limited, and it is difficult to meet all business requirements at the same time. Therefore, a task allocation method for power Internet of Things based on two-point cooperation is proposed. First, a task allocation model based on two-point cooperation was established to minimize the average task completion delay while meeting business resource requirements. Then the ECTA-MPSO (Edge Collaborative Task Allocation based on Modified Particle Swarm Optimization) algorithm is proposed, which solves the problem that the task allocation scheme easily falls into a local optimum. Simulation results show that the average delay decreases by 32.8% and 12% respectively compared with benchmark and GA algorithm.