Dynamic QoS-Driven Wireless Access Scheduling for Numerous Smart Devices in Energy Internet

Energy internet has received increasing attention as a promising solution for the widespread use of renewable energy resources in recent years. One of critical issues in energy internet communications is how to guarantee the desired quality of service(QoS) while numerous smart devices access the wireless network. In this paper, we study the problem of access scheduling for QoS guarantees under massive wireless access in energy internet. Firstly, we formulate this massive access problem as a queuing problem. Then based on method of queue overflow probability estimation, a dynamic resource allocation algorithm is proposed, where the allocation period can be adjusted flexibly with the adjustable step size in terms of the current queue length and current traffic conditions, to provide better QoS for massive access. Finally we conduct the simulations with three performance metrics in a multi-user LTE-A scenario. Our simulation results show that the proposed algorithm provides a prompt response to the variation of the simultaneous wireless access requests and leads to better performance for guaranteeing the desired quality of service.