OpenFlow网络中控制器负载均衡策略研究

控制器是软件定义网络(SDN)的核心,控制平面的可用性、可扩展性对SDN至关重要。本文首先提出了一种基于角色的分布式控制平面,并在此架构下,提出了一种交换机迁移的控制器负载均衡策略,从而解决控制平面可扩展性问题。     

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。     

软件定义网络中的异常流量检测研究进展

软件定义网络(software defined networking,简称SDN)是一种新型的网络架构.SDN将控制层从数据层分离并开放网络接口,以实现网络集中控制并提高网络的可扩展性和编程性.但是SDN也面临诸多的网络安全威胁.异常流量检测技术可以保护网络安全,防御恶意流量攻击.对SDN异常流量检测进行了全面的研究,归纳了数据平面和控制平面可能遭受到的网络攻击;介绍并分析了位于应用平面、控制平面和中间平台的异常流量检测框架;探讨了异常流量识别机制、负载均衡机制、异常流量追溯机制和异常缓解机制;最后指明SDN异常流量检测在未来工作中的研究方向.     

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应用平面与控制平面安全交互方法

软件定义网络(SDN)在推动网络创新的同时也为网络安全带来新的挑战.文章针对SDN应用平面与控制平面安全交互方法进行研究,以确保SDN提供可靠的网络服务.首先,文章提出SDN应用平面与控制平面安全交互方法总体架构;其次,利用TLS协议完成应用与控制器代理间的双向认证及安全通信,同时设计应用权限管理与应用身份信息管理,确...     

一种面向SDN域内控制平面可扩展性的机制

目前互联网中网络设备的体系结构是封闭的,不利于网络创新.软件定义的网络(SDN)对互联网垂直紧耦合的结构进行了解耦,同时将控制层面及其协议的实现开放.SDN促进互联网创新和快速演进的思想已被学术界和工业界广泛接受.OpenFlow作为SDN的代表性实例,已被全球多所大学和研究机构部署.但OpenFlow域内集中控制的模式,随着部署规模的增大,控制平面的可扩展性越来越明显.为此本文采用了负载均衡的思想解决该可扩展性问题.提出了一种高度可扩展的架构MSDN.MSDN首先对数据流初始化请求进行分流,然后通过共享的整个网络视图对请求并行处理,并对网络视图进行了数据集群,从而彻底解决了控制平面的可扩展性问题.文章最后的实验模拟证明了方案的可行性.     

软件定义网络控制平面的研究综述

软件定义网络(Software-defined network,SDN)作为一种新兴的网络范式,通过解耦控制平面与数据转发平面,集中控制并且聚集全网视图,在控制平面与数据平面建立开放接口,启用外部应用使得网络具有可编程性,从而弥补当前网络架构所存在的不足与限制。其中,控制器作为SDN中重要的组成部分,成为了研究的热点。针对软件定义网络控制平面控制器的研究,首先总结了当前SDN控制平面控制器技术发展的现状并对其进行归类;其次着重分析了当前控制器存在的一致性、可扩展性、负载均衡等一系列问题;最后探讨了软件定义网络技术未来的研究发展方向及趋势。     

SDN交换机转发规则TCAM存储优化综述

软件定义网络(SDN)将传统网络的控制平面和数据平面解耦,通过控制平面的控制器灵活地对网络进行管理,目前应用最广泛的控制协议是OpenFlow.三态内容寻址存储器(TCAM)查找速度快、支持三态掩码存储,在SDN网络中应用广泛.但TCAM成本高、功耗大,并且在存储含有范围字段匹配域的规则时候存在范围膨胀问题,因此交换机中可存储的转发规则数量,尤其是匹配域的数量和类型都比较多的OpenFlow规则数目非常有限,这成为约束SDN网络大规模扩展和应用的瓶颈.研究机构从不同角度提出了针对SDN中交换机转发规则的TCAM存储优化方案.本文从转发规则存储架构优化、本地交换机转发规则压缩、全局转发规则动态优化以及控制器参与的网络转发规则管理四个角度总结了相关研究工作,并提出了适合未来SDN网络的转发规则存储的综合优化方案.     

软件定义网络(SDN)研究进展

网络抽象促使软件定义网络(software-defined networking,简称SDN)的产生.SDN将数据平面与控制平面解耦合,简化了网络管理.首先从SDN诞生发展的背景入手,梳理了SDN的体系结构,包括数据层、控制层和应用层,并按照SDN的层次结构深入阐述其关键技术,特别分析了一致性、可用性和容错性等特性.然后,论述了SDN在不同应用场景下的最新研究成果.最后,展望未来研究工作.     

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.     

Scalable control plane for intra-domain communication in software defined information centric networking

Recently there has been a new emerging trend in integrating Information Centric Networking (ICN) and Software Defined Networking (SDN) together in the future Internet research area. Software defined information centric networking (SD-ICN) may face more serious scalability problem in control plane compared with traditional SDN environment due to new features about in-network caching and content-based communication. In this paper, we propose a scalable area-based hierarchical architecture (SAHA) for intra-domain communication to address the control plane scalability problem in SD-ICN. The SAHA supports scalable awareness of network resources and content resources, as well as guarantees efficient interest matching and resource adaptation. Simulation experiments under OMNET++ show that the proposed SAHA can achieve outstanding scalability in resource awareness and content-based communication.     

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...     

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%).     

Controller placement in software defined networks using multi-objective antlion algorithm

Software defined network (SDN) is a new modern network technology which decouples control plane and data plane to simplify network management. The separation of control plane from data plane arises the control placement problem (CPP) in these networks. The main questions in the CPP are (1) how many controllers are required to be used in such networks and (2) where these controllers should be placed. To achieve an efficient solution for such problem in SDN, we define the CPP as a multi-objective combinational optimization problem in this paper and solve the CPP by applying the antlion optimization algorithm on it. We consider three metrics for the CPP: (a) Inter-controllers latency, (b) switch to controller latency, and (c) multiple disjoint connectivity paths between switches and controllers. We evaluate our proposed solution by performing several experiments using different real network topologies. Experimental results show that our proposed solution provides better performance compared to the existing solutions.

     

A Rate Allocation Framework for Multi-Class Services in Software-Defined Networks

Software defined networking (SDN) is a network architecture with a programmable control plane (e.g., controllers) and simple data plane (e.g., forwarders). One of the popular SDN protocols/standards is OpenFlow, for which researchers have recently proposed some quality-of-service (QoS) supports. However, the proposals for rate allocation have some limitations in network scalability and multi-class services’ supports. In the literature, rate allocation formulations are commonly based on the framework of network utility maximization (NUM). Nevertheless, multi-class services are rarely considered in that framework since they make the formulated NUM become nonconvex and prevent its subgradient-based algorithm from converging. In this paper, we propose a scalable QoS rate allocation framework for OpenFlow in which multi-class services are considered. The convergence issue in the algorithm of our NUM-based framework is resolved by an admission control scheme. The network scalability is improved by our decentralized algorithms that can run on multiple parallel controllers. Extensive simulation and emulation results are provided to evaluate the performance of our method.     

An SDN-enhanced load-balancing technique in the cloud system

The vast majority of Web services and sites are hosted in various kinds of cloud services, and ordering some level of quality of service (QoS) in such systems requires effective load-balancing policies that choose among multiple clouds. Recently, software-defined networking (SDN) is one of the most promising solutions for load balancing in cloud data center. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. By using these technologies, SDN and cloud computing can improve cloud reliability, manageability, scalability and controllability. SDN-based cloud is a new type cloud in which SDN technology is used to acquire control on network infrastructure and to provide networking-as-a-service (NaaS) in cloud computing environments. In this paper, we introduce an SDN-enhanced Inter cloud Manager (S-ICM) that allocates network flows in the cloud environment. S-ICM consists of two main parts, monitoring and decision making. For monitoring, S-ICM uses SDN control message that observes and collects data, and decision-making is based on the measured network delay of packets. Measurements are used to compare S-ICM with a round robin (RR) allocation of jobs between clouds which spreads the workload equitably, and with a honeybee foraging algorithm (HFA). We see that S-ICM is better at avoiding system saturation than HFA and RR under heavy load formula using RR job scheduler. Measurements are also used to evaluate whether a simple queueing formula can be used to predict system performance for several clouds being operated under an RR scheduling policy, and show the validity of the theoretical approximation.     

SDN在战术MANET路由中的应用

近年来软件件定义网络(software-defined network,SDN)技术被逐渐应用至战术移动自组织网络(MANET)路由研究中,以求为日趋丰富的战术机动任务提供相较于传统MANET路由协议更好的QoS质量.然而由于MANET的强变化性、分布式结构等特点,SDN技术在MANET路由的应用中存在着许多问题亟待解...