云计算环境中软件定义网络研究应用

云计算可以根据实际需求提供灵活多样的服务,正成为IT模式的应用趋势,其中大部分采用软件定义网络(SDN)作为其网络架构,控制平面和数据平面相互分离,以简化网络管理、保证网络隔离.该文基于SDN技术的发展现状,介绍了OpenFlow交换、控制器和SDN技术的关键组成和研究进展,及其在网络中的应用.最后,分析了云计算环境中SDN技术存在的问题,并提出相关解决建议.     

SDN软件定义网络的发展与前景

软件定义网络(Software-Defined Networking,SDN)的产生极大的促进了网络技术的发展和应用.SDN将数据平面与控制平面结合,简化了网络控制.首先介绍SDN的发展过程、概念及的影响;然后论述SDN的应用前景.     

分布式SDN控制器放置问题研究

软件定义网络(Software-Defined Networking,SDN)通过控制平面与数据平面的分离和逻辑集中的控制构建了新的网络范式.考虑性能、可扩展性和可靠性等方面的需求,大规模网络通常采用分布式SDN控制平面,即通过放置多个控制器共同管理整个网络.这需要确定控制器的放置数量、放置位置以及交换机到控制器的分配...     

SDN性能优化技术研究综述

软件定义网络(Software-Defined Network,SDN)是一种新兴的网络架构,完全解耦了数据平面与控制平面。控制平面集中制定并下发全网决策,数据平面单纯负责数据转发。通过控制平面的开放接口,SDN实现了网络的可编程性。在未来SDN大面积部署应用的过程中,各个平面的性能优化技术将面临诸多挑战。首先,分析了SDN架构中控制平面和数据平面的性能优化技术的发展现状。其次,总结了各平面性能优化过程中所面临的问题。最后,展望了SDN性能优化方面的未来研究趋势。     

基于OpenFlow的SDN技术研究

软件定义网络(software-defined networking,简称SDN)技术分离了网络的控制平面和数据平面,为研发网络新应用和未来互联网技术提供了一种新的解决方案.综述了基于OpenFlow 的SDN 技术发展现状,首先总结了逻辑控制和数据转发分离架构的研究背景,并介绍了其关键组件和研究进展,包括OpenFlow交换机、控制器和SDN技术,然后从4 个方面分析了基于OpenFlow 的SDN 技术目前所面临的问题和解决思路.结合近年来的发展现状,归纳了在校园网、数据中心以及面向网络管理和网络安全方面的应用,最后探讨了未来的研究趋势.     

企业应用SDN的安全利弊

软件定义网络（SDN）将网络从硬件平面转移到了软件平面,受到软件控制器的管理。其好处包括自动化和简化网络管理工作以及提高应用程序性能。但同时,作为一项新的技术,SDN也很容易受到攻击。首先,根据Casaba Security公司共同创始人ChrisWeber表示,将控制集中到SDN控制器中能够模糊了防护的分层硬件的界限,例如防火墙。     

基于OpenFlow的SDN专利技术分析

软件定义网络(SDN)作为一种新的网络架构,为打破传统的TCP/IP架构提供了可能,实现了控制平面与数据平面的解耦,可以满足未来互联网的需求。基于OpenFlow的SDN可以为新的网络应用与未来互联网技术的发展提供支持。基于此,从专利角度系统梳理基于OpenFlow的SDN技术的专利申请,对国内外专利申请量趋势、重要申请人分布及研究和发展重点进行可视化展示。     

软件定义无线传感器网络研究综述

无线传感器网络（Wireless Sensor Network, WSN）经过长时间的发展,技术上已经有了很大进步,并广泛应用于很多领域,但其仍存在一些技术难点,影响应用效果。软件定义网络（Software-Defined Network, SDN）是一种新的网络架构,它采用了数据平面与控制平面解耦的思路,提供了网络架构发展的新方向。为了提升WSN的技术有效性,SDN架构被引入到WSN领域中,形成了新的软件定义无线传感器网络（Software-Defined Wireless Sensor Networks, SDWSN）。在分析软件定义无线传感器网络现有研究成果的基础上,阐述了WSN及SDN的发展现状;结合目前的研究进展,综述了SDWSN可行的技术方案;探讨了SDWSN未来的研究方向及发展趋势。     

SDN控制器的调研和量化分析

软件定义网络（software defined networking,SDN）是一种将网络控制平面和数据平面分离的新型网络架构。在SDN网络中,控制器的性能对网络性能有着重要的影响,当前很多公司和科研机构都已经提出了自己的控制器解决方案。然而针对如此众多的控制器,目前没有系统、全面的比较。由于缺乏足够的依据,研究人员只能凭借自己的经验或直觉来选择控制器。为了解决这个问题,对目前主流的SDN控制器在架构和性能上进行了系统的分析比较,并采用Cbench和Mininet对部分开源控制器进行了性能测试,同时针对单一控制器的性能问题,对现有的多控制器控制平面设计进行了分析综述。该研究结果对于研究人员选取正确的控制器具有重要的参考意义。     

基于SDN的天地一体化网络控制器部署方法综述

软件定义网络(Software Define Network,SDN)推动了传统网络的发展,将SDN引入天地一体化网络能够极大程度地调动各层级网络的资源,实现天地一体化网络的智能管控;首先,介绍了天地一体化网络和软件定义网络,论述了基于SDN的天地一体化网络架构的研究现状;随后,介绍了SDN控制器的性能指标并对比了当前的SDN多控制器部署方法,综述了基于SDN的天地一体化信息网络的控制器部署策略;最后,对未来基于SDN的天地一体化网络控制器部署方法进行了展望和归纳总结。     

软件定义网络控制平面可扩展性研究进展

软件定义网络（software-defined networking,简称SDN）遵循控制转发分离的设计原则,其控制平面采用集中的控制逻辑,在提供灵活高效的网络控制的同时,也面临着严重的可扩展性问题.对SDN控制平面可扩展性相关工作进行综述.首先分析控制平面可扩展性的影响因素并给出改善思路;在此基础上,从数据平面缓存优化、高性能控制器、分布式控制平面和控制资源优化分配4种技术路线出发,论述了主要的解决方案和研究进展.最后,给出总结并展望了未来的研究工作.     

MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters

Software-defined networking (SDN) introduces a new method in networking that by offering programmability and centralization, it can dynamically control and configure networks. In traditional networks, data plane did the whole forwarding process, but SDN decouples data plane and control plane by using programmable software controllers for deciding how to forward different flows. By implementing control plane in a software-based independent layer, the network management will become much easier and new policies can be applied to the network by changing a few lines of code. Since the resource allocation and meeting the required service-level agreement are really important in large-scale networks such as cloud datacenters, using SDN can be very useful. In these networks, one logically centralized controller cannot handle the whole network traffic and it will become network bottleneck. Therefore, multiple distributed controllers should be allocated in different regions of the network. Since the request rate of switches varies in time, by dynamic allocation of controllers, network resources will be allocated efficiently and this approach can also reduce power consumption. In this paper, we are going to propose a framework for provisioning software controllers in cloud datacenters by using metaheuristic algorithms. These algorithms can be less accurate compared to other kinds, but their main characteristics like simplicity, flexibility, derivation free, and local optimum avoidance make them a good nominee for solving controller provisioning problem and controller placement problem. Our framework improves computation time and reaches better results compared to other allocation techniques, but it is less accurate in some scenarios. Therefore, we believe metaheuristic approach can be very useful in developing new technologies for SDN in the future.     

基于多模电台的SDMANET网络组网方法

软件定义网络（SDN）在有线网络和数据中心网络等多种网络场景中正在快速发展,然而在移动自组织网络（MANET）中SDN的使用仍然处于起步阶段。因MANET网络拓扑变化频繁、资源受限以及采用分布式组网方式等特点使得在其中应用SDN变得具有挑战性。为此,本文提出一种基于多模电台的软件定义移动自组织网络（SDMANET）组网方法。该方法使用支配集算法计算骨干节点,仅由骨干节点使用带外信道和SDN控制器通信,并在MAC层基于骨干节点进行TDMA时隙动态分配。实验结果表明,与OLSR协议和直接带外控制的SDN方法相比,本方法具有更低的网络控制开销和信道访问时延,在大规模MANET网络中性能较好。     

K-DDoS-SDN: A distributed DDoS attacks detection approach for protecting SDN environment

Software-defined networking (SDN) is an advanced networking paradigm that decouples forwarding control logic from the data plane. Therefore, it provides a loosely-coupled architecture between the control and data plane. This separation provides flexibility in the SDN environment for addressing any transformations. Further, it delivers a centralized way of managing networks due to control logic embedded in the SDN controller. However, this advanced networking paradigm has been facing several security issues, such as topology spoofing, exhausting bandwidth, flow table updating, and distributed denial of service (DDoS) attacks. A DDoS attack is one of the most powerful menaces to the SDN environment. Further, the central data controller of SDN becomes the primary target of DDoS attacks. In this article, we propose a Kafka-based distributed DDoS attacks detection approach for protecting the SDN environment named K-DDoS-SDN. The K-DDoS-SDN consists of two modules: (i) Network traffic classification (NTClassification) module and (ii) Network traffic storage (NTStorage) module. The NTClassification module is the detection approach designed using scalable H2O ML techniques in a distributed manner and deployed an efficient model on the two-nodes Kafka Streams cluster to classify incoming network traces in real-time. The NTStorage module collects raw packets, network flows, and 21 essential attributes and then systematically stores them in the HDFS to re-train existing models. The proposed K-DDoS-SDN designed and evaluated using the recent and publically available CICDDoS2019 dataset. The average classification accuracy of the proposed distributed K-DDoS-SDN for classifying network traces into legitimate and one of the most popular attacks, such as DDoS_UDP is 99.22%. Further, the outcomes demonstrate that proposed distributed K-DDoS-SDN classifies traffic traces into five categories with at least 81% classification accuracy.     

Enhancing the performance of futurewireless networks with software-defined networking

To provide ubiquitous Internet access under the explosive increase of applications and data traffic, the current network architecture has become highly heterogeneous and complex, making network management a challenging task. To this end, software-defined networking (SDN) has been proposed as a promising solution. In the SDN architecture, the control plane and the data plane are decoupled, and the network infrastructures are abstracted and managed by a centralized controller. With SDN, efficient and flexible network control can be achieved, which potentially enhances network performance. To harvest the benefits of SDN in wireless networks, the software-defined wireless network (SDWN) architecture has been recently considered. In this paper, we first analyze the applications of SDN to different types of wireless networks. We then discuss several important technical aspects of performance enhancement in SDN-based wireless networks. Finally, we present possible future research directions of SDWN.     

A <Emphasis Type="Italic">K</Emphasis> self-adaptive SDN controller placement for wide area networks

As a novel architecture, software-defined networking (SDN) is viewed as the key technology of future networking. The core idea of SDN is to decouple the control plane and the data plane, enabling centralized, flexible, and programmable network control. Although local area networks like data center networks have benefited from SDN, it is still a problem to deploy SDN in wide area networks (WANs) or large-scale networks. Existing works show that multiple controllers are required in WANs with each covering one small SDN domain. However, the problems of SDN domain partition and controller placement should be further addressed. Therefore, we propose the spectral clustering based partition and placement algorithms, by which we can partition a large network into several small SDN domains efficiently and effectively. In our algorithms, the matrix perturbation theory and eigengap are used to discover the stability of SDN domains and decide the optimal number of SDN domains automatically. To evaluate our algorithms, we develop a new experimental framework with the Internet2 topology and other available WAN topologies. The results show the effectiveness of our algorithm for the SDN domain partition and controller placement problems.     

A subtree-based approach to failure detection and protection for multicast in SDN

Software-defined networking (SDN) has received tremendous attention from both industry and academia. The centralized control plane in SDN has a global view of the network and can be used to provide more effective solutions for complex problems, such as traffic engineering. This study is motivated by recent advancement in SDN and increasing popularity of multicasting applications. We propose a technique to increase the resiliency of multicasting in SDN based on the subtree protection mechanism. Multicasting is a group communication technology, which uses the network infrastructure efficiently by sending the data only once from one or multiple sources to a group of receivers that share a common path. Multicasting applications, e.g., live video streaming and video conferencing, become popular, but they are delay-sensitive applications. Failures in an ongoing multicast session can cause packet losses and delay, which can significantly affect quality of service (QoS). In this study, we adapt a subtree-based technique to protect a multicast tree constructed for OpenFlow switches in SDN. The proposed algorithm can detect link or node failures from a multicast tree and then determines which part of the multicast tree requires changes in the flow table to recover from the failure. With a centralized controller in SDN, the backup paths can be created much more effectively in comparison to the signaling approach used in traditional multiprotocol label switching (MPLS) networks for backup paths, which makes the subtree-based protection mechanism feasible. We also implement a prototype of the algorithm in the POX controller and measure its performance by emulating failures in different tree topologies in Mininet.     

软件定义网络安全问题研究综述

软件定义网络是一种新型的网络体系结构,其通过OpenFlow技术来实现网络控制面与数据面的分离,从而达到对网络流量的灵活控制,目前已成为下一代互联网的研究热点。随着SDN的发展及广泛应用,其安全问题已成为亟待解决的重要研究内容。近年来,国内外学者在SDN安全研究领域取得了一定的成果,文中针对SDN的3层架构分别对各层所面临的安全问题及其解决方案进行了系统总结。首先给出了SDN的定义和3层框架;接着依次总结了数据层、控制层和应用层的安全问题以及相应的解决方案;然后分析并讨论了传统网络安全与SDN安全的异同;最后对软件定义网络安全问题未来研究可能面临的挑战进行了展望。     

A survey on software defined networking and its applications

Software defined networking (SDN) achieves network routing management with logically centralized control software that decouples the network data plane from the control plane. This new design paradigm greatly emancipates network innovation. This paper introduces the background of SDN technology with its design principles, explains its differentiation, and summarizes the research efforts on SDN network architecture, components and applications. Based on the observation of current SDN development, this paper analyzes the potential driving forces of SDN deployment and its future trend.