Loop free alternate(LFA)is a routing protection scheme that is currently deployed in commercial routers.However,LFA cannot handle all single network component failure scenarios in traditional networks.As Internet serv...Loop free alternate(LFA)is a routing protection scheme that is currently deployed in commercial routers.However,LFA cannot handle all single network component failure scenarios in traditional networks.As Internet service providers have begun to deploy software defined network(SDN)technology,the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time.Therefore,this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios.First,the deployment of LFA scheme in a hybrid SDN network is described as a 0-1 integer linear programming(ILP)problem.Then,two greedy algorithms,namely,greedy algorithm for LFA based on hybrid SDN(GALFAHSDN)and improved greedy algorithm for LFA based on hybrid SDN(IGALFAHSDN),are proposed to solve the proposed problem.Finally,both algorithms are tested in the simulation environment and the real platform.Experiment results show that GALFAHSDN and IGALFAHSDN can cope with all single network component failure scenarios when only a small number of nodes are upgraded to SDN nodes.The path stretch of the two algorithms is less than 1.36.展开更多
Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced net...Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced network management strategies. An architecture for application-aware routing which can support dynamic quality of service( Qo S) in SDN networks is proposed. The applicationaware routing as a multi-constrained optimal path( MCOP) problem is proposed,where applications are treated as Qo S flow and best-effort flows. With the SDN controller applications,it is able to dynamically lead routing decisions based on application characteristics and requirements,leading to a better overall user experience and higher utilization of network resources. The simulation results show that the improvement of application-aware routing framework on discovering appropriate routes,which can provide Qo S guarantees for a specific application in SDN networks.展开更多
With the birth of Software-Defined Networking(SDN),integration of both SDN and traditional architectures becomes the development trend of computer networks.Network intrusion detection faces challenges in dealing with ...With the birth of Software-Defined Networking(SDN),integration of both SDN and traditional architectures becomes the development trend of computer networks.Network intrusion detection faces challenges in dealing with complex attacks in SDN environments,thus to address the network security issues from the viewpoint of Artificial Intelligence(AI),this paper introduces the Crayfish Optimization Algorithm(COA)to the field of intrusion detection for both SDN and traditional network architectures,and based on the characteristics of the original COA,an Improved Crayfish Optimization Algorithm(ICOA)is proposed by integrating strategies of elite reverse learning,Levy flight,crowding factor and parameter modification.The ICOA is then utilized for AI-integrated feature selection of intrusion detection for both SDN and traditional network architectures,to reduce the dimensionality of the data and improve the performance of network intrusion detection.Finally,the performance evaluation is performed by testing not only the NSL-KDD dataset and the UNSW-NB 15 dataset for traditional networks but also the InSDN dataset for SDN-based networks.Experimental results show that ICOA improves the accuracy by 0.532%and 2.928%respectively compared with GWO and COA in traditional networks.In SDN networks,the accuracy of ICOA is 0.25%and 0.3%higher than COA and PSO.These findings collectively indicate that AI-integrated feature selection based on the proposed ICOA can promote network intrusion detection for both SDN and traditional architectures.展开更多
空天地一体化网络作为6G技术的关键组成,在整合天基、空基和地基网络时,面临节点异构性、业务多样性等挑战,进而引发资源分配、竞争及故障风险等问题。基于此,聚焦基于软件定义网络(software defined network,SDN)与网络功能虚拟化(netw...空天地一体化网络作为6G技术的关键组成,在整合天基、空基和地基网络时,面临节点异构性、业务多样性等挑战,进而引发资源分配、竞争及故障风险等问题。基于此,聚焦基于软件定义网络(software defined network,SDN)与网络功能虚拟化(network functions virtualization,NFV)的空天地一体化网络任务部署与恢复,首先阐述了空天地一体化网络系统架构,介绍了各层网络构成、SDN和NFV原理及其相关应用,然后,针对上述挑战,以服务功能链技术为抓手,提出了面向任务的服务功能链优化部署、利用智能算法实现动态调度、通过匹配博弈算法完成失效恢复等策略,最后,构建了一个用例,设定节点部署、服务功能链建模等,验证了所提策略在提升服务功能链完成效率以及应对资源故障方面的有效性,旨在为空天地一体化网络资源管理提供理论基础。展开更多
The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are ...The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.展开更多
针对SDN流量工程中流量预测基于静态时空依赖的问题,提出了一种基于注意力机制的图卷积神经网络(GCN)与门控递归单元(GRU)集成的动态网络流量预测方法——AGCNGRU(attention mechanism for GCNGRU model)。借助GCN捕获网络中节点之间的...针对SDN流量工程中流量预测基于静态时空依赖的问题,提出了一种基于注意力机制的图卷积神经网络(GCN)与门控递归单元(GRU)集成的动态网络流量预测方法——AGCNGRU(attention mechanism for GCNGRU model)。借助GCN捕获网络中节点之间的流量空间依赖性和GRU捕获流量经过网络中各节点的时间依赖性,通过时间注意力机制设计每个隐藏状态的权重,以调整时间点流量信息的重要性,同时通过数据驱动空间注意力机制动态自适应调整Laplace矩阵,实现动态提取网络信息数据时空相关性,最终完成动态流量精准预测。在GEANT的数据集上的实验表明,所提出的方法在均方误差方面比GCNGRU减少24.8%,比GRU减少66.4%,并通过与传统路由算法OSPF、DDPG算法比较,在90%的流量负载强度下,网络性能比OSPF提升了24%,比DDPG提升了8.1%,进一步说明了AGCNGRU算法网络流量准确预测带来的时效性和有效性。展开更多
随着信息通信技术的飞速发展,下一代通信网络(如5G/6G)对网络性能提出了更高的要求,特别是在低延迟、高带宽、海量设备接入和智能化管控等方面。文章分析了软件定义网络(Software Defined Network,SDN)在大带宽、低时延和大规模物联网...随着信息通信技术的飞速发展,下一代通信网络(如5G/6G)对网络性能提出了更高的要求,特别是在低延迟、高带宽、海量设备接入和智能化管控等方面。文章分析了软件定义网络(Software Defined Network,SDN)在大带宽、低时延和大规模物联网环境中的应用,提出了协议优化策略并采用理论建模与仿真实验相结合的方法,评估不同优化方案的效果。结果表明:SDN优化能有效降低网络延迟,提高带宽利用率,增强物联网设备管理能力。展开更多
针对通信网络传输流量调度的难题,创新性地提出结合软件定义网络(Software Defined Network,SDN)与机器学习算法的调度方案,借助SDN控制器的强大功能,全面采集了网络数据层的关键信息。利用先进的机器学习算法,深入分析这些数据,准确预...针对通信网络传输流量调度的难题,创新性地提出结合软件定义网络(Software Defined Network,SDN)与机器学习算法的调度方案,借助SDN控制器的强大功能,全面采集了网络数据层的关键信息。利用先进的机器学习算法,深入分析这些数据,准确预测了未来的网络流量走势。基于这些精准的预测结果,制定了细致入微的流量调度策略,从而实现了网络流量的动态优化和高效管理。实验数据充分证明,与传统方法相比,所提出的方法在降低网络丢包率、提升资源利用率及传输性能等方面均表现出显著优势。这一创新成果不仅有效增强了网络流量的稳定性和规律性,还为通信网络传输流量调度领域开辟了新的研究路径。展开更多
随着轨道交通智能化发展,传统通信网络面临控制僵化、业务隔离等挑战。提出基于软件定义网络(Software Defined Network,SDN)技术的轨道交通通信网络架构优化设计方案,通过多域控制器协同机制和服务质量(Quality of Service,QoS)动态调...随着轨道交通智能化发展,传统通信网络面临控制僵化、业务隔离等挑战。提出基于软件定义网络(Software Defined Network,SDN)技术的轨道交通通信网络架构优化设计方案,通过多域控制器协同机制和服务质量(Quality of Service,QoS)动态调度算法改进关键技术。实验结果表明,SDN网络架构在端到端时延、数据吞吐量及故障恢复能力方面均优于传统网络架构。展开更多
探讨基于软件定义网络(Software Defined Network,SDN)的动态流量控制在通信网络安全中的应用。SDN将网络控制平面与数据平面分离,实现可编程和集中化管理。基于SDN的动态流量控制具有实时监测与响应、灵活流量调度、增强安全策略执行...探讨基于软件定义网络(Software Defined Network,SDN)的动态流量控制在通信网络安全中的应用。SDN将网络控制平面与数据平面分离,实现可编程和集中化管理。基于SDN的动态流量控制具有实时监测与响应、灵活流量调度、增强安全策略执行等优势,可用于网络攻击检测和防御、数据泄露防范及网络资源优化分配。通过实时监测异常流量、结合入侵检测系统/入侵防御系统(Intrusion Detection System/Intrusion Prevention System,IDS/IPS)、监控数据流量、加密与访问控制等手段提升安全性,同时实现流量负载均衡和资源分配优化,为通信网络安全提供有力保障。展开更多
为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MD...为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MDQN(Multi-service QoS routing method based on DeepQ Network)。该方法部署在SDN控制器中,能学习历史决策经验,并在网络状态发生变化时及时调整路径。通过在SDN中部署该方法,有效平衡了网络负载,增加了网络的吞吐量,为SDN中的QoS路由问题提供了一种有效的解决方案。展开更多
针对激光通信网络在灵活组网管控、动态拓扑及传输时效等方面的需求,提出一种基于软件定义网络(Software Defined Networking,SDN)的激光通信网络管控软件设计方案。该软件通过SDN控制器实现网络集中式策略管理,消除传统网络中控制设备...针对激光通信网络在灵活组网管控、动态拓扑及传输时效等方面的需求,提出一种基于软件定义网络(Software Defined Networking,SDN)的激光通信网络管控软件设计方案。该软件通过SDN控制器实现网络集中式策略管理,消除传统网络中控制设备与转发设备的耦合,采用拓扑识别、智能算路和SDN流量工程等关键技术,完成对激光通信网络的高效管理。实验结果表明,所设计的软件可有效优化激光通信网络资源的弹性分配机制,降低传输时延并增强网络的可扩展性,有效满足激光通信网络动态多变的业务需求。展开更多
基金This work is supported by the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(No.QCXM201910)the National Natural Science Foundation of China(No.61702315,No.61802092)+2 种基金the Scientific Research Setup Fund of Hainan University(No.KYQD(ZR)1837)the Key R&D program(international science and technology cooperation project)of Shanxi Province China(No.201903D421003)Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(No.201802013).
文摘Loop free alternate(LFA)is a routing protection scheme that is currently deployed in commercial routers.However,LFA cannot handle all single network component failure scenarios in traditional networks.As Internet service providers have begun to deploy software defined network(SDN)technology,the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time.Therefore,this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios.First,the deployment of LFA scheme in a hybrid SDN network is described as a 0-1 integer linear programming(ILP)problem.Then,two greedy algorithms,namely,greedy algorithm for LFA based on hybrid SDN(GALFAHSDN)and improved greedy algorithm for LFA based on hybrid SDN(IGALFAHSDN),are proposed to solve the proposed problem.Finally,both algorithms are tested in the simulation environment and the real platform.Experiment results show that GALFAHSDN and IGALFAHSDN can cope with all single network component failure scenarios when only a small number of nodes are upgraded to SDN nodes.The path stretch of the two algorithms is less than 1.36.
基金Supported by the National Basic Research Program of China(No.2012CB315803)the Around Five Top Priorities of One-Three-Five Strategic Planning,CNIC(No.CNIC PY 1401)Chinese Academy of Sciences,and the Knowledge Innovation Program of the Chinese Academy of Sciences(No.CNIC_QN_1508)
文摘Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced network management strategies. An architecture for application-aware routing which can support dynamic quality of service( Qo S) in SDN networks is proposed. The applicationaware routing as a multi-constrained optimal path( MCOP) problem is proposed,where applications are treated as Qo S flow and best-effort flows. With the SDN controller applications,it is able to dynamically lead routing decisions based on application characteristics and requirements,leading to a better overall user experience and higher utilization of network resources. The simulation results show that the improvement of application-aware routing framework on discovering appropriate routes,which can provide Qo S guarantees for a specific application in SDN networks.
基金supported by the National Natural Science Foundation of China under Grant 61602162the Hubei Provincial Science and Technology Plan Project under Grant 2023BCB041.
文摘With the birth of Software-Defined Networking(SDN),integration of both SDN and traditional architectures becomes the development trend of computer networks.Network intrusion detection faces challenges in dealing with complex attacks in SDN environments,thus to address the network security issues from the viewpoint of Artificial Intelligence(AI),this paper introduces the Crayfish Optimization Algorithm(COA)to the field of intrusion detection for both SDN and traditional network architectures,and based on the characteristics of the original COA,an Improved Crayfish Optimization Algorithm(ICOA)is proposed by integrating strategies of elite reverse learning,Levy flight,crowding factor and parameter modification.The ICOA is then utilized for AI-integrated feature selection of intrusion detection for both SDN and traditional network architectures,to reduce the dimensionality of the data and improve the performance of network intrusion detection.Finally,the performance evaluation is performed by testing not only the NSL-KDD dataset and the UNSW-NB 15 dataset for traditional networks but also the InSDN dataset for SDN-based networks.Experimental results show that ICOA improves the accuracy by 0.532%and 2.928%respectively compared with GWO and COA in traditional networks.In SDN networks,the accuracy of ICOA is 0.25%and 0.3%higher than COA and PSO.These findings collectively indicate that AI-integrated feature selection based on the proposed ICOA can promote network intrusion detection for both SDN and traditional architectures.
文摘空天地一体化网络作为6G技术的关键组成,在整合天基、空基和地基网络时,面临节点异构性、业务多样性等挑战,进而引发资源分配、竞争及故障风险等问题。基于此,聚焦基于软件定义网络(software defined network,SDN)与网络功能虚拟化(network functions virtualization,NFV)的空天地一体化网络任务部署与恢复,首先阐述了空天地一体化网络系统架构,介绍了各层网络构成、SDN和NFV原理及其相关应用,然后,针对上述挑战,以服务功能链技术为抓手,提出了面向任务的服务功能链优化部署、利用智能算法实现动态调度、通过匹配博弈算法完成失效恢复等策略,最后,构建了一个用例,设定节点部署、服务功能链建模等,验证了所提策略在提升服务功能链完成效率以及应对资源故障方面的有效性,旨在为空天地一体化网络资源管理提供理论基础。
基金extend their appreciation to Researcher Supporting Project Number(RSPD2023R582)King Saud University,Riyadh,Saudi Arabia.
文摘The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.
文摘针对SDN流量工程中流量预测基于静态时空依赖的问题,提出了一种基于注意力机制的图卷积神经网络(GCN)与门控递归单元(GRU)集成的动态网络流量预测方法——AGCNGRU(attention mechanism for GCNGRU model)。借助GCN捕获网络中节点之间的流量空间依赖性和GRU捕获流量经过网络中各节点的时间依赖性,通过时间注意力机制设计每个隐藏状态的权重,以调整时间点流量信息的重要性,同时通过数据驱动空间注意力机制动态自适应调整Laplace矩阵,实现动态提取网络信息数据时空相关性,最终完成动态流量精准预测。在GEANT的数据集上的实验表明,所提出的方法在均方误差方面比GCNGRU减少24.8%,比GRU减少66.4%,并通过与传统路由算法OSPF、DDPG算法比较,在90%的流量负载强度下,网络性能比OSPF提升了24%,比DDPG提升了8.1%,进一步说明了AGCNGRU算法网络流量准确预测带来的时效性和有效性。
文摘随着信息通信技术的飞速发展,下一代通信网络(如5G/6G)对网络性能提出了更高的要求,特别是在低延迟、高带宽、海量设备接入和智能化管控等方面。文章分析了软件定义网络(Software Defined Network,SDN)在大带宽、低时延和大规模物联网环境中的应用,提出了协议优化策略并采用理论建模与仿真实验相结合的方法,评估不同优化方案的效果。结果表明:SDN优化能有效降低网络延迟,提高带宽利用率,增强物联网设备管理能力。
文摘针对通信网络传输流量调度的难题,创新性地提出结合软件定义网络(Software Defined Network,SDN)与机器学习算法的调度方案,借助SDN控制器的强大功能,全面采集了网络数据层的关键信息。利用先进的机器学习算法,深入分析这些数据,准确预测了未来的网络流量走势。基于这些精准的预测结果,制定了细致入微的流量调度策略,从而实现了网络流量的动态优化和高效管理。实验数据充分证明,与传统方法相比,所提出的方法在降低网络丢包率、提升资源利用率及传输性能等方面均表现出显著优势。这一创新成果不仅有效增强了网络流量的稳定性和规律性,还为通信网络传输流量调度领域开辟了新的研究路径。
文摘随着轨道交通智能化发展,传统通信网络面临控制僵化、业务隔离等挑战。提出基于软件定义网络(Software Defined Network,SDN)技术的轨道交通通信网络架构优化设计方案,通过多域控制器协同机制和服务质量(Quality of Service,QoS)动态调度算法改进关键技术。实验结果表明,SDN网络架构在端到端时延、数据吞吐量及故障恢复能力方面均优于传统网络架构。
文摘为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MDQN(Multi-service QoS routing method based on DeepQ Network)。该方法部署在SDN控制器中,能学习历史决策经验,并在网络状态发生变化时及时调整路径。通过在SDN中部署该方法,有效平衡了网络负载,增加了网络的吞吐量,为SDN中的QoS路由问题提供了一种有效的解决方案。
文摘针对激光通信网络在灵活组网管控、动态拓扑及传输时效等方面的需求,提出一种基于软件定义网络(Software Defined Networking,SDN)的激光通信网络管控软件设计方案。该软件通过SDN控制器实现网络集中式策略管理,消除传统网络中控制设备与转发设备的耦合,采用拓扑识别、智能算路和SDN流量工程等关键技术,完成对激光通信网络的高效管理。实验结果表明,所设计的软件可有效优化激光通信网络资源的弹性分配机制,降低传输时延并增强网络的可扩展性,有效满足激光通信网络动态多变的业务需求。
