浅析SDN/NFV在联通IP网云化中的应用思考

目前联通IP网络正面临网络转型、实现快速业务支撑的强烈需要,在这种环境下,SDN/NFV作为新一代的网络技术,在网络重构变革中能够发挥巨大的作用。联通IP网络引入SDN/NFV,可以让运营网络向新的业务拓展。基于此,笔者研究了新的核心网网元虚拟方案,实现了基于SDN/NFV的核心网云化架构。     

面向SDN/NFV环境的网络功能策略验证

SDN与NFV技术带来了网络管理的灵活性与便捷性，但SDN的动态转发策略可能导致网络功能策略失效，同时不同网络功能的策略可能互相影响，引起冲突问题。为了在基于SDN/NFV的云网络中对网络功能的策略进行验证，分析了网络功能与 SDN 设备之间、跨网络功能之间的策略冲突，建立了统一策略表达进行策略解析，设计策略验证方案、框架并进行原型实现，检验不同场景下的虚拟网络功能策略的正确性，并与现有策略冲突验证方案对比，用实验进行了有效性与性能分析。     

运营商新一代运营支撑系统发展浅谈

随着网络重构对运营商的影响,对现有OSS系统提出了更高要求,需要引入SDN/NFV的控制器、业务编排和网络协同器,打破现有OSS系统的封闭性与烟囱式,形成对实体网络和虚拟网络的跨专业、跨网络的端到端统一运营管理.     

SDN／NFV整合所面临的挑战

迄今为止,运营商和厂商将关注点都主要放在了软件定义网络（SDN）和网络功能虚拟化（NFv）上,几乎没有考虑它们将如何被运营这一问题。SDN和NFV具有破坏力的原因很大一部分在于他们挑战了网络管理程序和系统的现状。分析人士指出SDN通过为网络提供一个可选的、单一的、集中的实时接触点,改变了OSS和网络之间的界线,同时NFV则需要部署—套全新的云管理堆栈。     

电力系统网络及设备的SDN演进研究

智能电网的建设发展催生了大量的电力新业务,电力系统网络和设备面临巨大的挑战,传统的网络和设备逐渐跟不上电力新业务的发展。在分析电力系统业务与网络设备发展现状以及SDN/NFV技术特点的基础上,将电力系统网络设备划分为两种模型：传统网络设备模型和SDN/NFV网络设备模型,提出了电力系统网络及设备在控制平面和数据平面的演进原则,总结了电力系统网络及设备的演进方向,给出了电力系统内应用SDN/NFV网络设备模型的应用案例设计和分析,为电力系统网络及设备的发展及建设提供参考。     

Radware下一代SDN和NFV解决方案

日前,Radware针对移动运营商和服务提供商推出了下一代软件定义网络（SDN）和网络功能虚拟化（NFV）解决方案战略。Radware全新的运营商解决方案战略巧妙利用SDN与NFV,开发出集成安全与应用交付架构,无缝地将完整的网络安全防御和服务交付作为网络服务集成在构架中。     

节点效用最大化的服务功能链构建方法

网络严重依赖中间件盒子来提供关键的服务功能,随着软件定义网络（SDN）与网络功能虚拟化（NFV）技术的发展,如何利用新技术部署中间件盒子并引导流量通过特定顺序的中间件盒子完成服务功能链构建成为亟待解决的问题。针对SDN+NFV环境下的服务功能链构建问题,提出一种节点效用最大化的服务功能链协同构建方法NUM（Node Utility Maximization）。首先结合SDN+NFV技术设计了一种服务功能链协同构建机制;其次,根据机制中资源处理器所解决的中间件盒子部署和流量引导问题,建立了节点选择模型和效用最大化模型;最后,利用禁忌搜索改进组合模拟退火算法对该模型进行求解。仿真实验表明,NUM方法与主流方法相比在构建时间、构建成功率以及网络拥塞率上具有优越性,同时采用所提出的服务链构建方法在节点效用上提高约20%。     

面向运营商的开放式网络平台

正博科战略计划全面满足对可互操作的SDN和NFV解决方案的需求博科推出博科RVyattaR平台。这是博科长期战略的第一阶段,为云和电信运营商提供开放式的模块化网络平台。Vyatta平台支持增建应用云和用户云,是业内第一次实现这个开放式战略。Vyatta平台符合ETSI NFV ISG的要求,包含基于开放标准和开源计划的网络功能虚拟化(NFV)和新兴的软件定义网络(SDN)技术。Vyatta平台采用成熟的核心组件,例如Vyatta vRouter     

基于多云架构进行应用编排混合部署的研究

针对单云架构存在的技术不足,提出了多云架构的编排混合部署方案。构建出包括多云存储层、云软件平台、数据传递层和应用层的架构体系,在多云网络架构中,云软件平台包括数据层、控制层、数据接口层和应用层,并在网络设备的控制平面设置SDN控制器,通过VPC(Virtual Private Cloud 虚拟私有云)对底层网络进行计算、分析、处理、存储和共享等。并在编排器内引入自适应蚁群算法,应用基于SDN/NFV 的通讯网络实现数据重构,进而实现数据网络的集中控制和智能编排。通过试验,本研究的方法误差精度低, 应用效果较好。     

核心网未来的网络架构演进

当今时代下,移动数据流量正在井喷式地不断增长,移动通信网络逐渐围绕着NFV/SDN技术进行深入发展 的态势,本文着重探讨了核心网的业务需求、技术支持和网络架构,分析了核心网的网络架构当前的状况以及未来演进方向, 这将会有利于进一步实现核心网未来的发展和网络建设。     

Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes

Fog computing provides quality of service for cloud infrastructure. As the data computation intensifies, edge computing becomes difficult. Therefore, mobile fog computing is used for reducing traffic and the time for data computation in the network. In previous studies, software-defined networking (SDN) and network functions virtualization (NFV) were used separately in edge computing. Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance, reliability, and scalability. SDN/NFV is still in development. The traditional Internet of things (IoT) data analysis system is only based on a linear and time-variant system that needs an IoT data system with a high-precision model. This paper proposes a combined architecture of SDN and NFV on an edge node server for IoT devices to reduce the computational complexity in cloud-based fog computing. SDN provides a generalization structure of the forwarding plane, which is separated from the control plane. Meanwhile, NFV concentrates on virtualization by combining the forwarding model with virtual network functions (VNFs) as a single or chain of VNFs, which leads to interoperability and consistency. The orchestrator layer in the proposed software-defined NFV is responsible for handling real-time tasks by using an edge node server through the SDN controller via four actions: task creation, modification, operation, and completion. Our proposed architecture is simulated on the EstiNet simulator, and total time delay, reliability, and satisfaction are used as evaluation parameters. The simulation results are compared with the results of existing architectures, such as software-defined unified virtual monitoring function and ASTP, to analyze the performance of the proposed architecture. The analysis results indicate that our proposed architecture achieves better performance in terms of total time delay (1800 s for 200 IoT devices), reliability (90%), and satisfaction (90%).     

网络功能虚拟化下服务功能链的资源管理研究综述

伴随着云计算,软件定义网络和网络功能虚拟化等网络新技术的出现,未来网络运维向着虚拟化、智能化的方向不断迈进.网络功能虚拟化提供了一种服务节点虚拟化的方法,它采用通用服务器替代传统网络中的专用中间件,可以大大降低网络运营商的建设和运营成本,提升网络管理的灵活性和可扩展性.由于网络端到端服务通常需要不同的服务功能,采用虚拟化技术构建网络服务功能链,进行资源的合理分配和调度成为一个重要的研究课题,引起了学术界和工业界的广泛关注.从网络功能虚拟化的技术背景出发,介绍了网络功能虚拟化下服务功能链资源管理的基础架构、技术基础和应用场景.而后基于服务功能链编排的不同阶段,将现有理论研究划分为4个部分:组链、部署、调度和按需缩放分别展开论述,从问题出发介绍和分析了研究现状.最后,针对现有存在问题,提出了一些拟解决方案,并对未来的研究方向进行了展望.     

网络功能虚拟化技术综述

无论是企业网还是数据中心,为实现相关应用功能、提升网络性能和加强网络安全等部署了大量的网络功能设备,但这些网络功能设备大多基于硬件,存在功能固化、扩展能力差、统一管理困难等问题。为解决上述问题,学术界和工业界不约而同将目光投向了网络功能虚拟化NFV技术。通过解耦网络功能和物理设备,使网络功能不受物理设备的约束,便于网络设备服务的升级更新,同时,NFV为新的体系结构、系统和应用的产生提供了可能。首先介绍了NFV技术,并与云计算和SDN进行对比,然后从VNF的系统结构、数据平面、控制平面、部署方式、实现语言和应用6个维度详细阐述了当前的研究成果,最后总结并展望了NFV未来的研究发展方向。     

NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains

With the advent of virtualization techniques and software-defined networking (SDN), network function virtualization (NFV) shifts network functions (NFs) from hardware implementations to software appliances, between which exists a performance gap. How to narrow the gap is an essential issue of current NFV research. However, the cumbersomeness of deployment, the water pipe effect of virtual network function (VNF) chains, and the complexity of the system software stack together make it tough to figure out the cause of low performance in the NFV system. To pinpoint the NFV system performance, we propose NfvInsight, a framework for automatic deployment and benchmarking VNF chains. Our framework tackles the challenges in NFV performance analysis. The framework components include chain graph generation, automatic deployment, and fine granularity measurement. The design and implementation of each component have their advantages. To the best of our knowledge, we make the first attempt to collect rules forming a knowledge base for generating reasonable chain graphs. NfvInsight deploys the generated chain graphs automatically, which frees the network operators from executing at least 391 lines of bash commands for a single test. To diagnose the performance bottleneck, NfvInsight collects metrics from multiple layers of the software stack. Specifically, we collect the network stack latency distribution ingeniously, introducing only less than 2.2% overhead. We showcase the convenience and usability of NfvInsight in finding bottlenecks for both VNF chains and the underlying system. Leveraging our framework, we find several design flaws of the network stack, which are unsuitable for packet forwarding inside one single server under the NFV circumstance. Our optimization for these flaws gains at most 3x performance improvement.     

CloudSimSDN-NFV: Modeling and simulation of network function virtualization and service function chaining in edge computing environments

Software-defined networking (SDN) has evolved and brought an innovative paradigm shift in computer networks by utilizing a programmable software controller with open protocols. Network functions, previously served on dedicated hardware, have shifted to network function virtualization (NFV) that enabled functions to be virtualized and provisioned dynamically upon generic hardware. In addition to NFV, edge computing utilizes the edge resources close to end-users, which can reduce the end-to-end service delay and the network traffic volume. Although these innovative technologies gained significant attention from both academia and industry, there are limited tools and simulation frameworks for the effectiveness evaluation in a repeatable and controllable manner. Furthermore, large-scale experimental infrastructures are expensive to setup and difficult to maintain. Even if they are created, they are not available or accessible for the majority of researchers throughout the world. In this paper, we propose a framework for simulating NFV functionalities in both edge and cloud computing environments. In addition to the basic network functionalities supported by SDN in CloudSimSDN, we added new NFV features, such as virtualized network functions allocation, migration, and autoscaling with the support of corresponding network functionalities, such as flow load balancing, rerouting, and service function chaining (SFC) maintenance. We evaluated our simulation framework with autoscaling and placement policies for SFC in the integrated edge and cloud computing environments. The results demonstrate its effectiveness in measuring and evaluating the end-to-end delay, response time, resource utilization, network traffic, and power consumption with different algorithms in each scenario.     

一种基于卫星网络的虚拟网络功能快速映射算法

针对卫星网络中卫星载重有限,不允许大规模部署物理硬件,导致其网络功能欠缺且网络管理和配置不灵活的问题,文中提出了基于软件定义网络(Software Defined Networking,SDN)/网络功能虚拟化(Network Function Virtualization,NFV)协同部署的卫星网络新架构。它通过SDN数控分离思想对网络进行动态管控,利用NFV技术在SDN的数字平面虚拟出网络功能,使网络功能能够从硬件设备中解耦出来,从而提高网络的灵活性。为了解决此框架中虚拟网络功能(Virtual Network Function,VNF)映射到底层物理网络上的时延过大且无法满足高动态卫星网络实时性的问题,进一步提出了Viterbi和图形模式匹配(Graph Pattern Matching,GPM)相结合的动态映射方法(Viterbi and GPM Dynamic Placement Approach,VG-DPA)。该算法将映射过程建模为隐马尔可夫服务链,采用Viterbi算法预计算满足软硬件限制的映射路径,然后根据预计算结果通过GPM来制定VNF编排策略。该算法解决了卫星网络中将所需的VNF映射到底层物理网络中时延过大的问题。实验结果表明,VG-DPA与传统的RAND和OMD算法相比能在很大程度上降低时延,减少资源消耗。