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.     

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.     

针对大规模软件定义网络的子域划分及控制器部署方法

针对大规模软件定义网络（SDN）的多控制器部署模型计算复杂度高的问题,定义了控制链路可靠性等多个衡量网络服务质量的指标,并提出一种针对大规模SDN的子域划分及控制器部署方法。首先,该方法利用改进的标签传播算法（LPA）将网络划分成多个子域,然后在子域中分别部署控制器。在考虑控制链路平均时延、可靠性以及控制器负载均衡等多个性能指标的基础上,将问题模型的计算复杂度降低至仅与网络规模呈线性关系。实验结果表明,所提算法与原始的LPA相比,控制器负载均衡性得到明显优化;与容量受限的控制器部署（CCP）算法相比,模型的计算复杂度和网络服务质量得到明显改善：在Internet2拓扑中,控制链路平均时延最多减小9%,控制链路可靠性最多增强10%。     

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.     

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...     

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。     

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.     

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.

     

An efficient and coordinated mapping algorithm in virtualized SDN networks

Software-defined networking (SDN) enables the network virtualization through SDN hypervisors to share the underlying physical SDN network among multiple logically isolated virtual SDN networks (vSDNs), each with its own controller. The vSDN embedding, which refers to mapping a number of vSDNs to the same substrate SDN network, is a key problem in the SDN virtualization environment. However, due to the distinctions of the SDN, such as the logically centralized controller and different virtualization technologies, most of the existing embedding algorithms cannot be applied directly to SDN virtualization. In this paper, we consider controller placement and virtual network embedding as a joint vSDN embedding problem, and formulate it into an integer linear programming with objectives of minimizing the embedding cost and the controller-to-switch delay for each vSDN. Moreover, we propose a novel online vSDN embedding algorithm called CO-vSDNE, which consists of a node mapping stage and a link mapping stage. In the node mapping stage, CO-vSDNE maps the controller and the virtual nodes to the substrate nodes on the basis of the controller-to-switch delay and takes into account the subsequent link mapping at the same time. In the link mapping stage, CO-vSDNE adopts the k-shortest path algorithm to map the virtual links. The evaluation results with simulation and Mininet emulation show that the proposed CO-vSDNE not only significantly increases the long-term revenue to the cost ratio and acceptance ratio while guaranteeing low average and maximum controller-to-switch delay, but also achieves good vSDN performance in terms of end-to-end delay and throughput.     

Resource Allocation for Reliable Communication Between Controllers and Switches in SDN

In software-defined networking (SDN), the communication between controllers and switches is very important, for switch can only work by relying on flow tables received from its controller. Therefore, how to ensure the reliability of the communication between controllers and switches is a key problem in SDN. In this paper, we study this problem from two aspects: the controller placement and the resource backup aspect. Firstly, in order to implement the reliable communication and meet the required propagation delay between controllers and switches, a min-cover based controller placement approach is proposed. Then, in order to protect both controllers and control paths from regional failure, a backup method based on an exponential decay failure model is proposed, which considers the regional influence and the survivability of backup controllers and control paths. Simulations show that our controller placement approach can meet the reliability and delay requirement with appropriate controller allocation scheme, and our backup method can improve the survivability of backup controllers and control paths while ensuring the performance of control network.     

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.     

智能软件定义网络

近年来,人工智能(artificial intelligence,简称AI)以强劲势头吸引着学术界和工业界的目光,并被广泛应用于各种领域.计算机网络为人工智能的实现提供了关键的计算基础设施.然而,传统网络固有的分布式结构往往无法快速、精准地提供人工智能所需要的计算能力,导致人工智能难以实际应用和部署.软件定义网络(so...     

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。     

Improving the performance of load balancing in software-defined networks through load variance-based synchronization

Software-Defined Networking (SDN) is a new network technology that decouples the control plane logic from the data plane and uses a programmable software controller to manage network operation and the state of network components. In an SDN network, a logically centralized controller uses a global network view to conduct management and operation of the network. The centralized control of the SDN network presents a tremendous opportunity for network operators to refactor the control plane and to improve the performance of applications. For the application of load balancing, the logically centralized controller conducts Real-time Least loaded Server selection (RLS) for multiple domains, where new flows pass by for the first time. The function of RLS is to enable the new flows to be forwarded to the least loaded server in the entire network. However, in a large-scale SDN network, the logically centralized controller usually consists of multiple distributed controllers. Existing multiple controller state synchronization schemes are based on Periodic Synchronization (PS), which can cause undesirable situations. For example, frequent synchronizations may result in high synchronization overhead of controllers. State desynchronization among controllers during the interval between two consecutive synchronizations could lead to forwarding loops and black holes. In this paper, we propose a new type of controller state synchronization scheme, Load Variance-based Synchronization (LVS), to improve the load-balancing performance in the multi-controller multi-domain SDN network. Compared with PS-based schemes, LVS-based schemes conduct effective state synchronizations among controllers only when the load of a specific server or domain exceeds a certain threshold, which significantly reduces the synchronization overhead of controllers. The results of simulations show that LVS achieves loop-free forwarding and good load-balancing performance with much less synchronization overhead, as compared with existing schemes.     

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.     

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.     

SDN故障分析研究综述

软件定义网络（software defined networking,SDN）架构的三大基本特性成为了网络故障发生的主要影响因素,从而引入新的故障威胁和风险,降低网络可靠性。首先,介绍了SDN的基本架构及其三大基本特性可能引发的安全问题;其次,从架构的物理角度出发,分别探讨控制平面域、控制通道域和数据平面域所面临的故障风险;随后,基于各故障域的故障类型,探讨现有的解决方案;最后,对未来的研究工作进行了展望。     

SDN控制器部署和基于流的动态管理方案*

软件定义网络（Software Defined Networking, SDN）通过构建独立的控制平面,极大地降低了网络设备及管理的复杂性。但在大规模广域网部署中,这种逻辑集中的方法在性能和扩展性方面存在诸多限制。因此控制平面多控制器的部署是一个非常重要的任务,其可以通过配置有限的资源来满足多样化需求。这些需求包括延迟限制、容错能力和负载均衡。本文首先提出一种控制器部署方法,该方法用于在给定的网络拓扑中完成控制器位置的部署。其次针对该部署方法设计了两种算法：交换机迁移算法将过载控制器域内交换机迁移到未过载控制器管理域中去,实现控制器间负载均衡;控制器池伸缩容量算法（Controller pool Scalable Capacity Algorithm, CSCA）实现池内控制器数目的动态伸缩,提高网络资源利用率。最后,仿真结果表明,相较LG方法,该方案在完成部署任务的同时,能够减少系统管理开销。     

基于混合制排队模型的SDN控制器性能评估研究

软件定义网络SDN将逻辑控制与数据转发相分离,提高了网络的灵活性和可编程能力,成为近年来未来网络领域的研究热点。SDN在实际应用部署时将面临控制器性能瓶颈的挑战,因而有必要理解SDN控制器的性能特性。为此,首先对SDN控制器中Packet-In消息的到达过程和处理时间进行分析,进而基于排队论提出了一种容量有限的SDN控制器性能评估模型M/M/1/m,推导得出了该模型的性能参数,包括:平均等待队长、平均等待时间、平均队列长度和平均逗留时间。最后,采用控制器性能测试工具Cbench对该模型进行了实验评估。实验结果表明:相对于现有其它模型,该模型的估计时延更接近于实际测量时延,可更精确地描述SDN控制器的性能。     

Dependability modeling of Software Defined Networking

Software Defined Networking (SDN) is a new network design paradigm that aims at simplifying the implementation of complex networking infrastructures by separating the forwarding functionalities (data plane) from the network logical control (control plane). Network devices are used only for forwarding, while decisions about where data is sent are taken by a logically centralized yet physically distributed component, i.e., the SDN controller. From a quality of service (QoS) point of view, an SDN controller is a complex system whose operation can be highly dependent on a variety of parameters, e.g., its degree of distribution, the corresponding topology, the number of network devices to control, and so on. Dependability aspects are particularly critical in this context. In this work, we present a new analytical modeling technique that allows us to represent an SDN controller whose components are organized in a hierarchical topology, focusing on reliability and availability aspects and overcoming issues and limitations of Markovian models. In particular, our approach allows to capture changes in the operating conditions (e.g., in the number of managed devices) still allowing to represent the underlying phenomena through generally distributed events. The dependability of a use case on a two-layer hierarchical SDN control plane is investigated through the proposed technique providing numerical results to demonstrate the feasibility of the approach.