{"title":"基于PPO和GNN的SDN智能路由优化","authors":"Jiawei Wu, ZeLin Zhu","doi":"10.1016/j.jnca.2025.104249","DOIUrl":null,"url":null,"abstract":"With the continuous increase of network scale, a variety of emerging applications (e.g., video streaming) continue to emerge, which puts forward differentiated requirements for quality of service (QoS), such as extremely low latency, high bandwidth, low packet loss rate, etc. To this effect, an intelligent routing method is needed to meet various traffic QoS requirements. However, existing routing optimization QoS schemes either lack guaranteed QoS performance or cannot generalize to invisible network topologies. To address the problem, this article innovatively proposes the QoS intelligent routing method PPO-R, which combines PPO and GNN-based routing optimization for SDN. The algorithm generates multiple disjoint candidate paths by designing a redundant tree algorithm, infers the near optimal traffic splitting ratios on the pre-selected path, and reasonably allocates traffic to different paths based on the obtained traffic splitting ratios. Compared to the baseline scheme DQS, in the medium network topology Germany-50, the QoS performance of PPO-R is about 10.6% higher than that of DQS. The experimental results show that the PPO-R algorithm can achieve better QoS routing optimization results, consume less computing resources, and significantly improve the robustness and generalization of QoS routing.","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"65 1","pages":""},"PeriodicalIF":7.7000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent routing optimization for SDN based on PPO and GNN\",\"authors\":\"Jiawei Wu, ZeLin Zhu\",\"doi\":\"10.1016/j.jnca.2025.104249\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the continuous increase of network scale, a variety of emerging applications (e.g., video streaming) continue to emerge, which puts forward differentiated requirements for quality of service (QoS), such as extremely low latency, high bandwidth, low packet loss rate, etc. To this effect, an intelligent routing method is needed to meet various traffic QoS requirements. However, existing routing optimization QoS schemes either lack guaranteed QoS performance or cannot generalize to invisible network topologies. To address the problem, this article innovatively proposes the QoS intelligent routing method PPO-R, which combines PPO and GNN-based routing optimization for SDN. The algorithm generates multiple disjoint candidate paths by designing a redundant tree algorithm, infers the near optimal traffic splitting ratios on the pre-selected path, and reasonably allocates traffic to different paths based on the obtained traffic splitting ratios. Compared to the baseline scheme DQS, in the medium network topology Germany-50, the QoS performance of PPO-R is about 10.6% higher than that of DQS. The experimental results show that the PPO-R algorithm can achieve better QoS routing optimization results, consume less computing resources, and significantly improve the robustness and generalization of QoS routing.\",\"PeriodicalId\":54784,\"journal\":{\"name\":\"Journal of Network and Computer Applications\",\"volume\":\"65 1\",\"pages\":\"\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Network and Computer Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jnca.2025.104249\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Network and Computer Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.jnca.2025.104249","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Intelligent routing optimization for SDN based on PPO and GNN
With the continuous increase of network scale, a variety of emerging applications (e.g., video streaming) continue to emerge, which puts forward differentiated requirements for quality of service (QoS), such as extremely low latency, high bandwidth, low packet loss rate, etc. To this effect, an intelligent routing method is needed to meet various traffic QoS requirements. However, existing routing optimization QoS schemes either lack guaranteed QoS performance or cannot generalize to invisible network topologies. To address the problem, this article innovatively proposes the QoS intelligent routing method PPO-R, which combines PPO and GNN-based routing optimization for SDN. The algorithm generates multiple disjoint candidate paths by designing a redundant tree algorithm, infers the near optimal traffic splitting ratios on the pre-selected path, and reasonably allocates traffic to different paths based on the obtained traffic splitting ratios. Compared to the baseline scheme DQS, in the medium network topology Germany-50, the QoS performance of PPO-R is about 10.6% higher than that of DQS. The experimental results show that the PPO-R algorithm can achieve better QoS routing optimization results, consume less computing resources, and significantly improve the robustness and generalization of QoS routing.
期刊介绍:
The Journal of Network and Computer Applications welcomes research contributions, surveys, and notes in all areas relating to computer networks and applications thereof. Sample topics include new design techniques, interesting or novel applications, components or standards; computer networks with tools such as WWW; emerging standards for internet protocols; Wireless networks; Mobile Computing; emerging computing models such as cloud computing, grid computing; applications of networked systems for remote collaboration and telemedicine, etc. The journal is abstracted and indexed in Scopus, Engineering Index, Web of Science, Science Citation Index Expanded and INSPEC.