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作 者:王家兴 杨思锦[2] 庄雷[2] 宋玉[2] 阳鑫宇 WANG Jiaxing;YANG Sijin;ZHUANG Lei;SONG Yu;YANG Xinyu(School of Cyber Science and Engineering,Zhengzhou University,Zhengzhou 450002,China;School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450001,China)
机构地区:[1]郑州大学网络空间安全学院,郑州450002 [2]郑州大学计算机与人工智能学院,郑州450001
出 处:《计算机科学》2023年第7期286-292,共7页Computer Science
基 金:国家电网有限公司总部科技项目(5700-202024176A-0-0-00)。
摘 要:基于以太网协议的时间敏感网络(TSN)通过不同类型流满足工业网络的实时传输、互联互通等多种需求。但时间触发(TT)流、音视频桥接(AVB)流和尽力而为(BE)流在网络中传输时,同种流争用队列、不同种流相互干扰的情况难以避免。针对TSN中多种流量调度影响端到端时延确定性的问题,提出了一种在线混合流量分析的粒子群(PSO)改进算法。该算法根据网络状况动态为混合流量计算路径,通过减少冗余搜索和约束粒子速度,避免粒子陷入局部最优,并加快搜索速度以满足在线计算的时间限制;对不同类型流量设置对应的适应度函数,降低混合流量间的相互干扰,减少了排队时延。仿真结果表明,所提算法在TSN网络中有效提高了混合流量传输成功率,并拥有稳定的性能和良好的计算效率。The time-sensitive network(TSN)based on the Ethernet protocol meets various requirements such as real-time transmission and interconnection of industrial networks through different types of streams.However,when time-triggered(TT)streams,audio/video bridging(AVB)streams,and best-effort(BE)streams are transmitting in the network,it is unavoidable that the same stream competes for queues and different streams interfere with each other.Aiming at the problem that multiple traffic scheduling in TSN affects the end-to-end delay determinism,this paper proposes an improved particle swarm optimization(PSO)for online mixed-traffic analysis.The algorithm dynamically calculates paths for mixed traffic based on network conditions,and accelerates searches to meet the time limits of online computation by reducing redundant searches and constraining particle velocities to avoid particles falling into local optimizations.What’s more,the algorithm sets corresponding fitness functions for different types of traffic to reduce mutual interference between mixed traffic and queuing delay.Simulation results show that proposed algorithm can effectively improve the success rate of mixed traffic transmission in TSN network,and has stable performance and good computing efficiency.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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