DFRDRL: a dynamic fuzzy routing algorithm based on deep reinforcement learning with guaranteed latency and bandwidth for software-defined networks


연구 분야: Networking



학회: Journal of Big Data


초록

Traditional routing algorithms have several limitations that become increasingly significant in the context of Software-Defined Networking (SDN). Firstly, these algorithms often have limited support for Quality of Service (QoS) requirements, making them less suitable for handling diverse traffic types efficiently. Moreover, current SDN controllers leverage a default shortest-path routing approach, which does not allow for more dynamic and flexible traffic management based on real-time network policies. To address these issues, this paper introduces a Dynamic Fuzzy Routing algorithm based on Deep Reinforcement Learning (DRL) for SDN that provides guaranteed latency and bandwidth (DFRDRL). DFRDRL provides intelligent and efficient routing that adapts to dynamic traffic by considering path-state criteria and using DRL. Fuzzy logic mainly performs online routing between an ingress-egress pair. To adapt to dynamic traffic changes, DFRDRL can predict the traffic matrix in real time. Meanwhile, DFRDRL reduces the routing reliance on network topology by weighting the network based on critical nodes. Additionally, when the network experiences congestion based on the traffic matrix, a deferral mechanism is applied to prioritize requests with lower resource demands. This mechanism helps ensure efficient resource allocation by temporarily postponing or queuing higher-demand requests, thereby optimizing overall network performance during periods of congestion. The simulation results show that the performance of DFRDRL is better than the equivalent algorithms in terms of latency and throughput. Also, DFRDRL is about 2.5% more efficient than the best existing algorithm in terms of admission rate of routing requests.


Author Profile
Yonghong Wang

Department of Computer Science Xinzhou Normal University Xinzhou 034000 Shanxi China

China
Author Profile
Marini Othman

Faculty of Data Science and Information Technology INTI International University 71800 Nilai Negeri Sembilan Malaysia

Andorra
Author Profile
Wou Onn Choo

Faculty of Data Science and Information Technology INTI International University 71800 Nilai Negeri Sembilan Malaysia

Andorra

📄 논문 정보

발행 연도 2024년
인용수 5
출판 국가 Andorra, China
사이트 Springer
좋아요 수 0

연관 논문 목록 (435건)