Q-Learning Routing and Link Scheduling Based on Traffic Mode

The interference and resource congestion caused by multiple concurrent flows may cause sharp perfor-mance degradation of wireless mesh networks. In order to solve the problem, a Q-learning Routing and Scheduling concerning Traffic (QRST) scheme is proposed. Firstly, the Q-learning algorithm is used to find the path for each routing request. Then the combined scheduling is completed according to the path finding and channel allocation, and the connection of paths is allocated with cyber source for every slot in a heuristic way. In order to verify the co-rrectness and effectiveness of the scheme, virtual computing is performed under different network resource configurations and multiple traffic requests. The experimental results show that, compared with COSS and AODV, wireless mesh network using the QRST scheme has better performance in terms of throughput, activated link number and transmission completion time.