Yu Song1, Xusheng Qian2, Nan Zhang3, Wei Wang2, Ao Xiong1,*
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3007-3021, 2024, DOI:10.32604/cmc.2024.051217
- 15 May 2024
Abstract To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront the challenge of managing the surging demand for data traffic. Within this realm, the network imposes stringent Quality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanisms in accommodating such extensive data flows. In response to the imperative of handling a substantial influx of data requests promptly and alleviating the constraints of existing technologies and network congestion, we present an architecture for QoS routing optimization with in Software Defined Network (SDN), leveraging deep reinforcement learning. This… More >