Varna-based optimization:a novel method for capacitated controller placement problem in SDN

Recently,software defined networking(SDN)is a promising paradigm shift that decouples the control plane from the data plane.It can centrally monitor and control the network through softwarization,i.e.,controller.Multiple controllers are a necessity of current SDN based WAN.Placing multiple controllers in an optimum way is known as controller placement problem(CPP).Earlier,solutions of CPP only concentrated on propagation latency but overlooked the capacity of controllers and the dynamic load on switches,which is a significant factor in real networks.In this paper,we develop a novel optimization algorithm named varna-based optimization(VBO)and use it to solve CPP.To the best of our knowledge,this is the first attempt to minimize the total average latency of SDN along with the implementation of TLBO and Jaya algorithms to solve CPP for all twelve possible scenarios.Our experimental results show that TLBO outperforms PSO,and VBO outperforms TLBO and Jaya algorithms in all scenarios for all topologies.     

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...     

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.     

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.     

基于软件定义网络的边缘控制部署机制

针对软件定义网络（software-defined Networking,SDN）中单一控制器容易发生过载导致较长时延的问题,提出一种基于SDN的边缘控制模型,该模型采取分层部署方式将边缘计算集成到SDN中,每个边缘控制器控制其覆盖范围内部署的所有子边缘控制器和交换机,负责区域内网络设备的通信量。为了方便管理边缘控制器之间的交互,该模型引入一个控制器代理模块,将设备请求转发给父控制器或将路由信息发送给子控制器来协调控制器之间的工作。实验结果表明,与基于SDN的传统网络相比,该方法依托部署在网络设备边缘的计算和存储服务,减轻了SDN主控制器上的负载,降低了转发平面和控制平面之间的延时,显著地改善了总处理延时和带宽使用情况。     

基于自优化的SDN交换机动态迁移机制

为提高SDN控制器的使用效率以及多控制器之间的负载均衡度,对多控制器的部署问题进行了研究,并提出了一种交换机动态迁移机制.该动态迁移机制基于周期性运行的自优化的算法实现,按照控制器的部署情况,将网络划分成多个域,通过分析各域内相关参数,分别找出负载最高和最低的控制器节点,并根据控制器负载和交换机请求率快速选择出最佳的迁移交换机和迁移目的地.控制器的负载均衡度、交换机请求的处理时延和算法的复杂度是算法设计中所考虑的主要因素.该算法的优点在于通过局部的动态调整实现了对SDN控制层的灵活管理.仿真结果表明,基于自优化的交换机动态迁移方案能够有效提高多控制器间的负载均衡度,减小流请求的处理时延,同时将运算复杂度保持在一个相对合理的水平.     

Preserving Privacy of Software-Defined Networking Policies by Secure Multi-Party Computation

In software-defined networking (SDN), controllers are sinks of information such as network topology collected from switches. Organizations often like to protect their internal network topology and keep their network policies private. We borrow techniques from secure multi-party computation (SMC) to preserve the privacy of policies of SDN controllers about status of routers. On the other hand, the number of controllers is one of the most important concerns in scalability of SMC application in SDNs. To address this issue, we formulate an optimization problem to minimize the number of SDN controllers while considering their reliability in SMC operations. We use Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to determine the optimal number of controllers, and simulate SMC for typical SDNs with this number of controllers. Simulation results show that applying the SMC technique to preserve the privacy of organization policies causes only a little delay in SDNs, which is completely justifiable by the privacy obtained.

     

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.     

考虑拜占庭属性的SDN安全控制器多目标优化部署方案

通过赋予软件定义网络分布式控制平面拜占庭属性可以有效提高其安全性。在实现拜占庭属性过程中，控制器部署的数量、位置，以及交换机与控制器之间的连接关系会直接影响全局网络关键性能指标。为此，提出了一种考虑拜占庭属性的 SDN 安全控制器多目标优化部署方案。首先，构建了综合考量交互时延、同步时延、负载差异程度和控制器部署数量等优化指标的拜占庭控制器部署问题（MOSBCPP）模型；然后，针对该模型个性化设计了包括控制器部署策略初始化函数、变异函数，快速非支配排序函数及精英策略选择函数等在内的NASG-II求解算法。相关仿真结果表明，该部署方案能够在有效降低交互时延、同步时延、负载差异程度和控制器部署数量等性能指标的同时提高控制平面安全性。     

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。     

一种支持细粒度并行的SDN虚拟化编程框架

软件定义网络(software defined network,简称SDN)通过集中式的控制器提高了网络的可编程性,成为近年来网络领域非常热门的话题。以Openflow网络为代表的软件定义网络将逻辑控制与数据转发相隔离,为网络虚拟化技术提供了良好的平台。集中式的抽象与控制使得SDN虚拟化框架的处理效率成为主要瓶颈。现有的SDN虚拟化框架由于缺乏对细粒度并行的支持,为编程人员充分利用多核/众核资源、控制更大规模的网络带来了极大的挑战。为了提高SDN虚拟化框架的处理效率,提出一种新的SDN虚拟化编程框架,通过新颖的API和运行时,在框架内部支持细粒度的并行处理。该框架通过对网络中流和网络资源进行抽象,使开发人员可以直接通过划分流空间来定义不同的虚拟网络,利用无锁的编程方式对共享的网络资源和流进行操作。实验结果表明,该框架在逻辑控制的执行效率方面具有良好的可扩展性,可以创建出更大规模的虚拟网络,并对其进行更为复杂的控制。     

Optimal controller placement in large scale software defined networks based on modified NSGA-II

Software Defined Network (SDN) is an emerging approach to overcome challenges of traditional networks. One particularly important issue in SDN architectures is that of controller placement problem (CPP), i.e., deploying a desired number of controllers within a network while some possibly conflicting requirements have to be fulfilled. A single optimal placement may not be possible and decision makers need to seek for an appropriate trade-off among the metrics. Although an exhaustive evaluation of all possible placements can be practically performed well for small and medium-sized networks, regarding realistic time and resource restrictions, heuristic approaches are required for large-scale networks. Hence, a heuristic called Multi-Start Hybrid NSGA-II (MHNSGA-II) is introduced which yields faster computation times and needs reasonable memory to perform. The obtained results on several topologies extracted from Internet Topology Zoo showed the efficiency of the proposed approach.     

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.     

Energy-saving model for SDN data centers

With the development of the Internet, data centers have become vital infrastructures which provide computing, storage and other services for the networks. According to statistics, data centers consume large amount of electricity all around the world. In most cases, the majority of network devices in data centers are relatively idle, resulting in a waste of energy. Software defined network (SDN) was proposed by UC Berkeley and Stanford University around 2008, which allows the administrators to manage the network and set configurations through abstraction of lower level functionality. It also separates the control plane and the data plane, so administrators can control the network traffic through centralized controller instead of access to physical devices. This paper discusses the energy-saving model in data center networks based on SDN. We propose two different energy-saving algorithms, which can be applied to different data centers. Through centralized management and preprocessing traffic by SDN, we get better energy efficiency and reduce the energy cost by 30–40 %. To the best of our knowledge, this is the first work on energy saving in SDN architecture which provides two different algorithms that can be applied in different scenarios.     

An intelligent optimization-based traffic information acquirement approach to software-defined networking

Internet of things (IoT) is a global information infrastructure that supports access to thousands of monitoring devices and user terminals. A large amount of monitoring data generated by IoT is integrated to cloud computing through the network to improve the quality of life of citizens. Fine-grained and accurate traffic information is important for IoT network management. Software-defined networking (SDN) is a centralized control plane as a logical control center, making network management more flexible and efficient. Then, we collect fine-grained traffic information in SDN-based IoT networks to improve network management. To acquire the traffic information with low overhead and high accuracy, first, we collect the statistics of coarse-grained traffic of flows and fine-grained traffic of links, and then we utilize the intelligent optimization methods to estimate the network traffic. To improve the granularity and accuracy of the acquired traffic information, we construct an optimization function with constraints to decrease the estimation errors. As the optimization function of traffic information is a non-deterministic polynomial-hard problem, we present a heuristic algorithm to obtain the optimal solution of the fine-grained measurement. Finally, we conduct some simulations to verify the proposed measurement scheme. Simulation results show that our approach can improve the granularity and accuracy of traffic information with intelligent optimization methods.     

Improvement of battery lifetime in software-defined network using particle swarm optimization based cluster-head gateway switch routing protocol with fuzzy rules

The software-defined network (SDN) is one of the network architectures, in which the data plane and control plane is divided from each other, and the network can be handled using a sensibly centralized controller and this method is adopted to reconfigure the wireless sensor network automatically. In this article, to implement the SDN in MANET, in which control nodes can be chosen in SDN dynamically for the activation of MANET function to allocate the works to other mobile nodes to the base station. However, in the field of mobile ad hoc networks, the network lifetime, and battery lifetime is one of the major problems and the energy consumption can play a significant rule for the transmission of data in the SDN. Therefore, in this article, particle swarm optimization (PSO) based CGSR (cluster-head gateway switch routing protocol) algorithm with fuzzy rules is proposed to increase the network lifetime of battery powered mobile nodes by reducing the energy consumptions of each node in software-defined MANET. In this proposed method, a routing method that can permit various mobile nodes with low battery power to transmits the data from source node to base station. We design a PSO based CGSR routing protocol by selecting the routing mobile nodes using fuzzy rules for packet transmission. In CGSR process, the formation of cluster and selection of cluster head is executed depending on the particle swarm optimization method. This proposed routing protocol can be used to enhance the battery lifetime by extension of the network lifetime with numerical analysis for efficient route node selection.     

软件定义网络中资源消耗型攻击及防御综述

在传统网络中,集成多种网络功能的控制平面和负责转发数据包的数据平面是紧密耦合的,并且通常嵌入在一个专用设备中,这严重限制了网络管理的灵活性和网络服务的创新性。软件定义网络（Software-Defined Networking,SDN）作为一种新型的网络范式,通过将控制平面与数据平面解耦克服了传统网络架构的不足。研究人员凭借全网视图可见性以及对网络设备直接编程的能力提出了诸多SDN应用场景,如数据中心网络、云和广域网。然而SDN带来的灵活性、可管理性以及可编程性等优点是以引入新的安全挑战为代价。本文聚焦SDN网络中的资源消耗型攻击,首先分层整理了SDN网络中的关键资源以及攻击目标,然后对控制平面、控制通道和数据平面存在的多种资源消耗型攻击以及现有防御机制做出了详细的分析和归纳,最后对未来的研究工作进行了展望,并提出了一些潜在的研究方向。     

面向智慧医疗云的SDN动态负载均衡方法

文中 引入软件定义网络(Software Defined Network,SDN)对智慧医疗云进行网络管理,并且针对传统SDN控制器存在单点失效和负载均衡的问题,设计了智慧医疗分布式SDN控制器系统。SDN控制系统分为SDN控制器集群、数据转发平面和智慧医疗云服务系统3层。在此基础上,提出一种实时负载动态自调节的快速负载均衡算法DAF(Dynamic Adaptive and Fast Load Balancing)。在该算法中,负载信息感知组件周期性地采集自己的负载信息,自动地进行控制器间的负载信息交互;控制器的负载值超过阈值时,会触发交换机迁移动作,以动态配置交换机与控制器之间的映射关系。实验结果表明,面向智慧医疗云的分布式SDN控制系统的性能良好,且DAF算法能够快速地实现SDN控制器间的负载均衡,提升了智慧医疗云的网络吞吐量。     

A tool for tracing network data plane via SDN/OpenFlow

SDN provides an approach to create desired network forwarding plane by programming applications. For a large-scale SDN network comprised of multiple domains and running multiple controller applications, it is difficult to measure and diagnose the problems of flow tables in data plane. Tracing the forwarding path of SDN is one of effective way for data plane state measurement. Previously proposed methods for debugging SDN were applied to a single administrative domain. There is less effort to trace the flow entries of the data plane in large-scale multi-domain SDN networks. In this paper, we propose a method of software defined data plane tracing in large-scale multi-domain SDN networks. Our method can trace forwarding paths, and get the matched flow entries and other customized trace information. We present the designs compatible with OpenFlow 1.0 and 1.3 switches. The performance and deployment effect are evaluated by simulation test and analysis. It shows that our method has better performance than traditional IP traceroute, and its deployment at about 20% of AS nodes can enable 70% of AS paths to be traceable.     

软件定义网络:安全模型、机制及研究进展

软件定义网络(software defined networking,简称SDN)初步实现了网络控制面与数据面分离的思想,然而在提供高度开放性和可编程性的同时,网络自身也面临着诸多安全问题,从而限制了SDN在很多场景下的大规模部署和应用.首先对SDN的架构和安全模型进行分析;其次,从"SDN特有/非特有的典型安全问题"和"SDN各层/接口面临的安全威胁"两方面,对SDN中存在的典型安全威胁和安全问题进行分析和归纳;随后从6个方面对现有SDN安全问题的主要解决思路及其最新研究进展分别进行探讨,包括SDN安全控制器的开发、控制器可组合安全模块库的开发和部署、控制器Do S/DDo S攻击防御方法、流规则的合法性和一致性检测、北向接口的安全性和应用程序安全性;最后对SDN安全方面的标准化工作进行了简要分析,并对SDN安全方面未来的研究趋势进行了展望.