Improving network management with software defined networking

This paper presents in the area of software defined networking. Our aim is to identify limitations of current networking technologies and how software-defined networks (SDN) could reduce cost, and improve the performance of campus Networks for their network management. We pursue to identify solutions in this paper to enable possible customers to assess that SDN may be preferable over Current network and also SDN introduces new options and configuration methods. In this paper, we identify problems with the current state of the art network configuration and management mechanisms and introduce new mechanisms to improve various aspects of network management. The technologies we describe enable network operators to implement a wide range of network policies in a high-level policy language and easily determine sources of performance problems. In addition to the systems themselves. Here we refer a various prototype arrangements in campus networks that demonstrate how SDN can improve common network management tasks. In addition to that, we explains therotically that, how SDN can improve the network management performance in network.

In recent years, SDN has evolved as a promising alternative to the traditional networking paradigm. This is because the traditional network is decentralized, making it difficult to manage and provide trouble-shooting. SDN is an approach to network management whereby the forwarding process of the data plane (DP) is disassociated from the control plane (CP). The CP is responsible for decision-making. SDN centrally control the network infrastructure and make it programmable. Communication between the two planes (data and control) is carried out by the OpenFlow (OF) protocol. The deployment of SDN was initiated by Mr. Matrin Casado and his research team in 2008. The original projects developed at Stanford University were SANE and ETHANE. Security reports and web articles suggest that SDN (Software Defined Network) has the caliber to defend DDoS attacks. The year 2017 has been declared as the year of SDN adaption and DDoS mitigation. The initial effort in the direction of compiling the detection and mitigation approaches has been done in (Dayal et al., 2016). Recently a similar effort has been done in (Rochak et al., 2019). The CP of SDN has a complete visibility of the network which makes traffic monitoring feasible. Moreover, SDN open flow switches contain forwarding logic only; decision-making capability is softwarized at 58controller. This helps the controller to instruct and configure the switches with new flow rules which the switches follow. This facilitates the network admins to detect and mitigate these attacks easily. SDN have gained momentum among the possible solutions of DDoS attacks due to its decentralized nature of network management, but solutions come with its repercussions. The centralization and open architecture framework makes SDN difficult for widespread adaptation. The chapter begins with an introduction to DDoS attacks and its classification such as volumetric attack, protocol exploitation attack and application attack. In the next section, we discuss the possible DDoS attacks over SDN framework. We have categorized the vulnerability into three classes: DDoS attack on data, control, and application planes (APs). The DDoS attack on DP can further be classified into TCAM exhaustion, switch DDoS, ICMP flood, TCP flood, TCP_SYN flood, etc. We would discuss Resource depletion, OF bandwidth exhaustion, amplification attacks in DDoS attack over CP. HTTP flooding and Slowloris attack has been discussed in DDoS attack over AP. The next section highlights the working of attack tools used in performing DDoS attacks. Various DDoS tools have been widely exploited to render DDoS attacks and facilitate attackers to carry out dangerous attack on target; here target may be network resources, server resources, or applications. The fourth section focuses on the state-of-the-art for detection and mitigation approaches of DDoS attacks. Detection approaches are classified into statistical, policy, and machine learning-based approaches. DDoS mitigation OF switches, including Alcatel Lucent’s OmniSwitch, Brocade’s MLXe series routers, and applications such as DefensePro by Radware that are available in market; also depend on the statistical threshold to detect the DDoS attack. In addition, this section also incorporates a brief analysis of the previous defense mechanism of the last 10 years and analyzes and compares the products of different security vendors like Cloudflare, Radware, Akamai, Arbor, Nexusguard, etc.

Software‐defined networking (SDN) is a relatively new approach in network management that proposes to separate the network control (Control plane) and the forwarding process (Data plane) to optimize the network infrastructure and improve network performance, controllability, manageability and flexibility. However, like every technology, SDN has brought its own new challenges in terms of security and scalability which are very important aspects that should be considered to design and build a resilient architecture in order to meet carrier grade network requirements. In this paper, we propose a secure SDN architecture with IEEE 802.1X port‐based authentication where we also consider the controller's scalability issue by devolving the access control capability to the data plane. In this way, we reduce the high demand and the workload on the SDN controller. Our proposed model presents a novel SDN network architecture and logical network segmentation which provides an optimal and secure network access with low latency. We have implemented and tested our architecture to show its performance (authentication delays). Copyright © 2016 John Wiley & Sons, Ltd.

SummaryNetwork virtualization (NV) technologies have attracted a lot of attention as an essential solution for future networking infrastructure. The NV enables multiple tenants to share the same physical infrastructure and to create independent virtual networks (VNs) by decoupling the physical network in terms of topology, address, and control functions. One feasible way to realize full NV involves considering solutions based on the software‐defined networking (SDN) paradigm using its programmability. The SDN contributes many benefits to both network operations and management including programmability, agility, elasticity, and flexibility. There are several SDN‐based NV solutions; however, they suffered from a lack of scalability, high availability. Also, they have high latency between control and data plane because of proxy‐based architecture. In this thesis, we introduce a new NV platform, named Open Network Hypervisor (ONVisor). The design objectives include, among the features, (1) multitenancy, (2) scalability, (3) flexibility, (4) isolated VNs, and (5) VN federation. ONVisor was designed and implemented by extending Open Network Operating System, an open‐source SDN controller. The main features of ONVisor are (1) isolated control and data plane per VN, (2) support of distributed operations, (3) extensible translators, (4) on‐platform VN application development and execution, and (5) support of heterogenous SDN data‐plane implementations. Several experiments are conducted on various test scenarios in different test environments in terms of control and data plane performance compared to nonvirtualized SDN network. The results show that ONVisor can provide VNs a little bit lower control plane performance and similar data plane performance.

Software Defined Networking (SDN) is a new networking paradigm, with a great potential to increase network efficiency, ease the complexity of network control and management, and accelerate the rate of technology innovation. One of the core concepts of SDN is the separation of the network's control and data plane. The intelligence and the control of the network operation and management, such as routing, is removed from the forwarding elements (switches) and is concentrated in a logically centralised component, i.e. the SDN controller. In order for the controller to configure and manage the network, it needs to have up-to-date information about the state of the network, in particular its topology. Consequently, topology discovery is a critical component of any Software Defined Network architecture. In this paper, we evaluate the cost and overhead of the de facto standard approach to topology discovery currently implemented by the major SDN controller frameworks, and propose simple and practical modifications which achieve a significantly improved efficiency and reduced control overhead. We have implemented our new topology discovery approach on the widely used POX controller platform, and have evaluated it for a range of network topologies via experiments using the Mininet network emulator. Our results show that our proposed modifications achieve an up to 45% reduction in controller load compared to the current state-of-the-art approach, while delivering identical discovery functionality.

Along with the widespread development of Internet and mobile applications, the demand for more flexible and dynamic networking services increases. It becomes a new challenge for many carriers to deploy a variety of new services by effective provisioning of network resources. Software-Defined Networking (SDN) is a novel approach to make networks reconfigurable and extensible such that new services can be deployed with existing network devices. By decoupling the controller plane from the data plane in network devices, SDN brings networks programmability of the data plane and centralization of the controller plane. Conventional Operations Support Systems (OSSs) were developed to manage networks in a standard fashion with Simple Network Management Protocol (SNMP) or proprietary protocols. SDN provides a new framework in managing SDN-enabled devices. A new issue for carriers is how SDN-enabled networks and devices can be monitored and controlled by current OSSs. This paper focuses on performance management and aims to develop an efficient scheme to collect traffic statistics data via the SDN controller plane. Similar to Bulkstat, an SNMP-based mechanism for periodic collection and transfer of MIB objects, the proposed scheme for bulk traffic statistics collection is developed in the controller plane and provides a northbound interface for upper network management applications. Instead of using SNMP and MIBs, the scheme is implemented by periodically gathering statistics information of flow tables from SDN-enabled switches via the OpenFlow protocol.

Software-Defined networking (SDN) is a networking paradigm to enable dynamic, flexible, and programmatically efficient configuration of networks to revolutionize network control and management via separation of the control plane and data plane. The SDN technology has evolved in response to the demands from large data centers toward all types of networks, from IoT, enterprise, to ISP networks. On the one hand, SDN has provided solutions for high-demand resources, managing unpredictable data traffic patterns, and rapid network reconfiguration. It is further used to enhance network virtualization and security. On the other hand, SDN is still subject to many traditional network security threats. It also introduces new security vulnerabilities, primarily due to its logically centralized control plane infrastructure and functions. In this paper, we conduct a comprehensive survey on the core functionality of SDN from the perspective of secure communication infrastructure at different scales. A specific focus is put forward to address the challenges in securing SDN-based communications, with efforts taken up to address them. We further categorize the appropriate solutions for specific threats at each layer of SDN infrastructures. Lastly, security implications and future research trends are highlighted to provide insights for future research.

The use of Software-Defined Networking (SDN) has created a huge leap in the management of computer networks. SDN offers flexibility and the ability to dynamically manage networks, but along with its advantages, it also brings significant challenges in managing quality of service (QoS). QoS is critical to maintaining performance and user experience in increasingly complex and distributed network environments. The research method uses Solution Development to address a quality of service (QoS) management challenge and solution in Software Defined Networking with the approach of designing and developing practical solutions to address QoS management issues and challenges in SDN environments. Control Separation and Data Plane are centralized network control at the SDN controller, while the data plane reside in the networks hardware, both capable of maintaining QoS and a challenges in SDN with a computer network approach that separates the control layer from the data layer, enabling more flexible and centralized network management. Research conclusions related to SDN Software Defined Networking quality of service management problems and solutions, focusing on the problem of separating management and data levels. The separations of control and data plane concept in SDN has great potential to improve flexibility, scalability and more efficient network management.

The software defined networking (SDN) is a networking technique to disintegrate control plane and data (forwarding) plane in the network, allows use of open protocols to control network switches and routers using software controls and abstract infrastructure as per application and network services requirements. This makes it possible to implement network management and control through software. Word software means that network devices are programmable but software is not controlling everything centrally. This approach helps to achieve network and infrastructure manageability, control plane modularity, cost-effectiveness, generalized data planes and adaptable network, making virtualization easy to implement, as per need of an hour. The SDN yields a network infrastructure which will be programmable. This inherently qualifies for control to be shifted to software and network flow with network devices to be operated by software programs. A network engineer must now be able to re-program instead of re-build the network infrastructure manually. The following sections explain terminologies, working, and operations related to SDN. This paper helps readers to gain understanding and overview of SDN.

To accommodate big data, new technologies and features have started to be used in core network. Consequently, optical transport network has evolved towards Elastic Optical Network (EON). Despite the effort made towards efficient and reliable network management, interoperability problem in multi-vendor setting of the EON remains unsolved and it hinders the network management and monitoring. Hence, Network operators need to rely on the proprietary management solutions. This phenomenon poses complexity in network configuration, control, monitoring and management and also in turn results in higher Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) for the service providers. In this paper, standard data definition model of network elements of EON is presented for configuration, management and monitoring purpose. Standard YANG data models for the network elements, namely, Reconfigurable Optical Add/drop Multiplexer (ROADM), Bandwidth Variable Transponder (BVT) and Optical amplifier (OA) are presented. The implementation scenario for the developed data definition models are demonstrated for managing state of the art EON. It is contended that the adoption of these standard YANG data models within the NETCONF protocol not only facilitates the network configuration and management, but also improves the multi-vendor interoperability in the control and management plane of the EON.

Software-defined networking (SDN) is an emerging network architecture that decouples the control plane from the data plane, enabling centralized programmability and management of networks. While SDN offers benefits like flexibility, scalability, and automation, it also introduces new security vulnerabilities. This literature review analyzes the current state of research on SDN security in three key domains – Internet of Things (IoT) environments, cloud computing, and traditional enterprise networks. A systematic review methodology was followed to search, select, and review 53 relevant studies published in the past 5 years. The analysis focuses on identifying common SDN threat vectors, security solutions proposed leveraging SDN programmability and evaluating their effectiveness based on results from simulations, testbed experiments, and initial real-world implementations. Key findings of the review include lack of authentication, susceptibility to DDoS attacks, and flow rule conflicts as major security issues in SDN across domains. Dynamic traffic monitoring, access control, policy orchestration, and virtualized security functions are commonly proposed techniques to enhance SDN security. However, limitations exist in robustness testing at scale, emerging paradigms like fog computing, and quantitatively comparing SDN security with legacy networks. As SDN adoption expands, focused efforts are needed to address these research gaps through innovations in data-driven security, coordinated security policy, and emphasizing SDN controller security. This review provides valuable insights into the current state of SDN security research and informs future efforts needed in this important area

Rarely the interest in a new networking paradigm has increased at such a velocity as it is happening for software defined networking (SDN). Motivations of this hype of interest are several but the most important can be re-conducted to the following three: (i) SDN simplifies network configuration and management; (ii) SDN makes the network evolvable; (iii) SDN frees operators from vendors' lock-in. Eagerly, in some cases, or reluctantly, in others, both operators and manufacturers of communication and networking equipments have started new lines of research, development, and marketing focused on SDN. A quick look at the list of members of the organizations promoting the development of SDN-related standards suffices to understand that players of the wireless domain are trying to ride this wave as well. However, it is difficult for the observers to understand where such a wave is headed to in very common networking scenarios involving infrastructureless wireless communications. This paper is an attempt to fill this gap. In fact, a major objective of this paper is to analyze (i) what are the advantages of SDN in infrastructureless wireless networking environments such as wireless personal area networks (W-PANs), and (ii) what are the requirements that must be satisfied to apply SDN in W-PANs. Furthermore, a complete SDN solution for W-PANs, named Software Defined Wireless Network (SDWN), is introduced and a prototype implementation is described.

Recent advances in information and communications cloud-based services hold the potential to overcome the scalability and complex maintenance limitations of traditional networks. Software Defined Networking (SDN) surfaced as a promising paradigm to mitigate such limitations while offering flexible networks management. Particularly, SDN separates the control plane from the data plane to achieve abstraction of lower-level functionality, hence, allowing more efficient network management and utilization. However, SDN suffers from various performance and scalability problems leading to significant research efforts on maximizing the scalability of the control plane. This paper aims at reviewing different SDN controller scalability, topology-based and mechanism-based approaches, as well as discussing and analyzing how they attempt to solve the scalability challenge. Furthermore, this paper elaborates on the promising research trends and challenges. Our insights are also discussed to stimulate further research efforts addressing the control plane scalability in SDN.

Software-defined networking (SDN) scheme decouples network control plane and data plane, which can improve the flexibility of traffic management in networks. OpenFlow is a promising implementation instance of SDN scheme and has been applied to enterprise networks and data center networks in practice. However, it has less effort to spread SDN control scheme over the Internet to conquer the ossification of inter-domain routing. In this paper, we further innovate to the SDN inter-domain routing inspired by the OpenFlow protocol. We apply SDN flow-based routing control to inter-domain routing and propose a fine-granularity inter-domain routing mechanism, named SDI (Software Defined Inter-domain routing). It enables inter-domain routing to support the flexible routing policy by matching multiple fields of IP packet header. We also propose a method to reduce redundant flow entries for inter-domain settings. And, we implement a prototype and deploy it on a multi-domain testbed.

As a new networking paradigm, Software-Defined Networking (SDN) separates data and control planes to facilitate programmable functions and improve the efficiency of packet delivery. Recent studies have shown that there exist various security threats in SDN. For example, a saturation attack may disturb the normal delivery of packets and even make the SDN system out of service by flooding the data plane, the control plane, or both. The existing research has focused on saturation attacks caused by SYN flooding. This paper presents an anomaly detection method, called SA-Detector, for dealing with a family of saturation attacks through IP spoofing, ICMP flooding, UDP flooding, and other types of TCP flooding, in addition to SYN flooding. SA-Detector builds upon the study of self-similarity characteristics of OpenFlow traffic between the control and data planes. Our work has shown that the normal and abnormal traffic flows through the OpenFlow communication channel have different statistical properties. Specifically, normal OpenFlow traffic has a low self-similarity degree whereas the occurrences of saturation attacks typically imply a higher degree of self-similarity. Therefore, SA-Detector exploits statistical results and self-similarity degrees of OpenFlow traffic, measured by Hurst exponents, for anomaly detection. We have evaluated our approach in both physical and simulation SDN environments with various time intervals, network topologies and applications, Internet protocols, and traffic generation tools. For the physical SDN environment, the average accuracy of detection is 97.68% and the average precision is 94.67%. For the simulation environment, the average accuracy is 96.54% and the average precision is 92.06%. In addition, we have compared SA-Detector with the existing saturation attack detection methods in terms of the aforementioned performance metrics and controller's CPU utilization. The experiment results indicate that SA-Detector is effective for the detection of saturation attacks in SDN.