Task Offloading Based on Edge Computing Considering Overhead and Load Balancing in Industrial Internet of Things

Recently, the development of Industrial Internet of Things has made the emergence of innovative applications which are usually computation-intensive and latency-critical. In this paper, we study the task offloading in software-defined access network, where the industrial devices and edge computing servers are connected to wireless access points. To meet applications' requirements about latency and computing capacity and realize computational load balancing, we formulate a mixed integer non-linear program problem to minimize the overall cost. First, we propose an algorithm based on convex optimization and matching theory to minimize the overhead. Then, we consider load balancing of edge servers and extend our problem with regard to overhead and load balancing cost. We adopt alternating direction method of multipliers algorithm to solve the extended problem. Finally, simulation results demonstrate the effectiveness and superiority of our proposed algorithm.