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
为提高现阶段广播网络的运营效率,在降低广播网络运维成本的同时提升直播信号的质量和用户体验,提出在电视广播中的直播场景及广播信号处理环节分别部署软件定义网络(Software Defined Network,SDN)和网络功能虚拟化(Network Function V...为提高现阶段广播网络的运营效率,在降低广播网络运维成本的同时提升直播信号的质量和用户体验,提出在电视广播中的直播场景及广播信号处理环节分别部署软件定义网络(Software Defined Network,SDN)和网络功能虚拟化(Network Function Virtualization,NFV)网络架构。利用回传网络采集多场馆的信号,根据实时流量情况动态分配网络资源,同时在应对突发事件或临时增加直播需求时,SDN快速重新配置网络,优化调度直播流量。基于SDN架构,在广播信号处理环节通过NFV技术虚拟化视频编转码和用户权限认证,确保信号处理和分发环节的高效性。展开更多
In optical metro-access networks,Access Points(APs)and Data Centers(DCs)are located on the fiber ring.In the cloud-centric solution,a large number of Internet of Things(IoT)data pose an enormous burden on DCs,so the V...In optical metro-access networks,Access Points(APs)and Data Centers(DCs)are located on the fiber ring.In the cloud-centric solution,a large number of Internet of Things(IoT)data pose an enormous burden on DCs,so the Virtual Machines(VMs)cannot be successfully launched due to the server overload.In addition,transferring the data from the AP to the remote DC may cause an undesirable delivery delay.For this end,we propose a promising solution considering the interplay between the cloud DC and edge APs.More specifically,bringing the partial capability of computing in APs close to things can reduce the pressure of DCs while guaranteeing the expected Quality of Service(QoS).In this work,when the cloud DC resource becomes limited,especially for delay sensitive but not computing-dependent IoT applications,we degrade their VMs and migrate them to edge APs instead of the remote DC.To avoid excessive VM degradation and computing offloading,we derive appropriate VM degradation coefficients based on classic microeconomic theory.Simulation results demonstrate that our algorithms improve the service providers'utility with the ratio from 34%to 89%over traditional cloud-centric solutions.展开更多
Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified ne...Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.展开更多
The development of the Next-Generation Wireless Network(NGWN)is becoming a reality.To conduct specialized processes more,rapid network deployment has become essential.Methodologies like Network Function Virtualization...The development of the Next-Generation Wireless Network(NGWN)is becoming a reality.To conduct specialized processes more,rapid network deployment has become essential.Methodologies like Network Function Virtualization(NFV),Software-Defined Networks(SDN),and cloud computing will be crucial in addressing various challenges that 5G networks will face,particularly adaptability,scalability,and reliability.The motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms,including hypervisors,clouds,and containers,which will serve as a guide to dealing with the stimulating environment of 5G.This is particularly crucial when implementing network operations at the edge of 5G networks,where limited resources and prompt user responses are mandatory.Experimental results prove that containers outperform hypervisor-based virtualized infrastructure and cloud platforms’latency and network throughput at the expense of higher virtualized processor use.In contrast to public clouds,where a set of rules is created to allow only the appropriate traffic,security is still a problem with containers.展开更多
With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both local...With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both localand global allocation of resources in data centers.Hence,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in datacenters.Our approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant resources.With the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.展开更多
针对支持网络功能虚拟化(Network Function Virtualization,NFV)的软件定义网络(SDN)中,单播请求流通常需要由多个虚拟网络功能(Virtual Network Functions,VNFs)依序组成的服务功能链(Service Function Chain,SFC)进行处理。首先联合考...针对支持网络功能虚拟化(Network Function Virtualization,NFV)的软件定义网络(SDN)中,单播请求流通常需要由多个虚拟网络功能(Virtual Network Functions,VNFs)依序组成的服务功能链(Service Function Chain,SFC)进行处理。首先联合考虑VNF动态放置,多资源及QoS约束,以最小化资源消耗成本及自动确保网络负载均衡为目标定义了动态的SFC部署问题。接着设计考虑边际成本的资源相对成本函数并利用整数线性规划对该问题建模。然后,创新地设计了一个动态辅助边权图并基于拉格朗日松弛方法构建具有自动负载均衡的服务功能链嵌入算法(SFC Embedding Algorithm,SFC-EA)对原问题求解。仿真结果表明,SFC-EA能有效解决多资源及多QoS约束下的SFC顺序嵌入这个NP难问题,并能自动确保网络负载均衡,提高网络吞吐量和流接受率。展开更多
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。
文摘为提高现阶段广播网络的运营效率,在降低广播网络运维成本的同时提升直播信号的质量和用户体验,提出在电视广播中的直播场景及广播信号处理环节分别部署软件定义网络(Software Defined Network,SDN)和网络功能虚拟化(Network Function Virtualization,NFV)网络架构。利用回传网络采集多场馆的信号,根据实时流量情况动态分配网络资源,同时在应对突发事件或临时增加直播需求时,SDN快速重新配置网络,优化调度直播流量。基于SDN架构,在广播信号处理环节通过NFV技术虚拟化视频编转码和用户权限认证,确保信号处理和分发环节的高效性。
基金supported by the Researchers Supporting Project of King Saud University,Riyadh,Saudi Arabia,under Project RSPD2025R681。
文摘In optical metro-access networks,Access Points(APs)and Data Centers(DCs)are located on the fiber ring.In the cloud-centric solution,a large number of Internet of Things(IoT)data pose an enormous burden on DCs,so the Virtual Machines(VMs)cannot be successfully launched due to the server overload.In addition,transferring the data from the AP to the remote DC may cause an undesirable delivery delay.For this end,we propose a promising solution considering the interplay between the cloud DC and edge APs.More specifically,bringing the partial capability of computing in APs close to things can reduce the pressure of DCs while guaranteeing the expected Quality of Service(QoS).In this work,when the cloud DC resource becomes limited,especially for delay sensitive but not computing-dependent IoT applications,we degrade their VMs and migrate them to edge APs instead of the remote DC.To avoid excessive VM degradation and computing offloading,we derive appropriate VM degradation coefficients based on classic microeconomic theory.Simulation results demonstrate that our algorithms improve the service providers'utility with the ratio from 34%to 89%over traditional cloud-centric solutions.
基金This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number(DSR2022-RG-0102).
文摘Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.
基金supported by Future University Researchers Supporting Project Number FUESP-2020/48 at Future University in Egypt,New Cairo 11845,Egypt.
文摘The development of the Next-Generation Wireless Network(NGWN)is becoming a reality.To conduct specialized processes more,rapid network deployment has become essential.Methodologies like Network Function Virtualization(NFV),Software-Defined Networks(SDN),and cloud computing will be crucial in addressing various challenges that 5G networks will face,particularly adaptability,scalability,and reliability.The motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms,including hypervisors,clouds,and containers,which will serve as a guide to dealing with the stimulating environment of 5G.This is particularly crucial when implementing network operations at the edge of 5G networks,where limited resources and prompt user responses are mandatory.Experimental results prove that containers outperform hypervisor-based virtualized infrastructure and cloud platforms’latency and network throughput at the expense of higher virtualized processor use.In contrast to public clouds,where a set of rules is created to allow only the appropriate traffic,security is still a problem with containers.
基金the Fundamental Research Program of Guangdong,China,under Grants 2020B1515310023 and 2023A1515011281in part by the National Natural Science Foundation of China under Grant 61571005.
文摘With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both localand global allocation of resources in data centers.Hence,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in datacenters.Our approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant resources.With the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.
文摘针对支持网络功能虚拟化(Network Function Virtualization,NFV)的软件定义网络(SDN)中,单播请求流通常需要由多个虚拟网络功能(Virtual Network Functions,VNFs)依序组成的服务功能链(Service Function Chain,SFC)进行处理。首先联合考虑VNF动态放置,多资源及QoS约束,以最小化资源消耗成本及自动确保网络负载均衡为目标定义了动态的SFC部署问题。接着设计考虑边际成本的资源相对成本函数并利用整数线性规划对该问题建模。然后,创新地设计了一个动态辅助边权图并基于拉格朗日松弛方法构建具有自动负载均衡的服务功能链嵌入算法(SFC Embedding Algorithm,SFC-EA)对原问题求解。仿真结果表明,SFC-EA能有效解决多资源及多QoS约束下的SFC顺序嵌入这个NP难问题,并能自动确保网络负载均衡,提高网络吞吐量和流接受率。
