An implementation of software defined network with Raspberry Pi

The Internet has reached a breaking point, enabling ubiquitous accessibility to all digital demands. Though people have accelerated their use of overall digital demands due to the convenience of the Internet, where nearly everything is connected and accessible, it is becoming increasingly difficult to manage and modify networks. It is always a challenge to meet the emerging needs of network industry. SDN framework was proposed to overcome traditional network architecture (TNA) restrictions in order to cope with contemporary network management in terms of flexibility, agility, responding to faults, and dynamic changes. SDN assists network operators by uncoupling the control plane from its underlying ternary content-addressable memory (TCAM) hardware often called as forwarding plane by allowing the networks to programme as per the anticipated network functionality. Now, switching from traditional to software-defined networking styles, it is worth to check the robustness of the open flow (south bound interface)-based controller platform and the capability of its fault tolerance attribute to approach the successful SDN implementation. The performance of SDN open flow controllers plays a vital role in SDN implementation, which is meant for the separation between control and data plane to leverage the life of network industry. This paper comprehensively surveys the contrast between traditional network architecture (TNA) and software-defined network architecture. This research work discusses about the best feasible SDN implementation, as well as the selection of a useful controller platform for overcoming traditional network constraints and the performance assessment criteria for SDN open flow controllers. Further, the survey is continued with possible literature or work done by various researchers on performance analysis and evaluation of open flow-based SDN controllers as well as in a group of two or more controllers with respect to multifarious network condition, network criteria/parameter/metric, scaling of network load resources with most important varying network topology design. Ultimately, it strives to point ongoing research omission with respect to controller’s performance bottleneck benchmark suggesting optimized solution when it is well experimented.KeywordsTraditional network architecture (TNA)Software-defined networking (SDN)SDN open flow controllersOpen flow protocolPerformance evaluation/analysis

In the past few years there has been a tremendous increase in network attacks especially the Denial of Service and Distributed Denial of Service attacks. The attacker tries to send a number of packets to the victim site so as to make it unavailable to provide any service. Nowadays DoS attacks can be performed using IoT enabled devices too. The traditional network architecture is unable to handle such attacks which gave rise to Software Defined Network(SDN) as a solution. Software-defined networking is a network technology that provides central control over the network and thus manages network behavior dynamically through software via open interfaces. SDN plays a role to retain the heterogeneity in networks and objects by integrating into them a control solution that interacts with the SDN controllers. Although SDN provides promising solutions to many security problems, it is also exposed to new attacks targeting the data plane, control plane or the link connecting the two planes. This paper aims at the integration of IoT with SDN technology, the study of OpenFlow Protocol, different DoS attacks occurring on the layered SDN structure and the possible mitigation strategies to weaken the impact of those attacks on the network. For this purpose, we will be using a mininet simulator, OpenVSwitch(OVS) and Floodlight SDN controller.

The issue of supporting Quality of Service (QoS) for media applications and other different applications has increased tremendously in industry and the scholarly community. The traditional network architecture became overloaded and congested due to the continued demand for network resources and the limited bandwidth available. The user experience and the academic studies have indicated an increase in limitations and weaknesses of these architectures. A new network architecture paradigm, called Software-Defined Networks (SDN), has received massive attention from researchers and it is used to find new solutions to the limitations found in traditional network architectures. This survey presents an overview of QoS in a traditional network, as well as in SDN. The existing SDN platforms, controllers, and protocols are presented as well as the multimedia flow routing mechanisms being investigated. The survey outcomes will be useful for people in the industry as well as academic researchers identifying current limitations and challenges of QoS within SDN and traditional network architectures.

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 is a new paradigm that overcomes problems associated with traditional network architecture by separating the control logic from data plane devices. It also enhances performance by providing a highly-programmable interface that adapts to dynamic changes in network policies. As software-defined networking controllers are prone to single-point failures, providing security is one of the biggest challenges in this framework. This paper intends to provide an intrusion detection mechanism in both the control plane and data plane to secure the controller and forwarding devices respectively. In the control plane, we imposed a flow-based intrusion detection system that inspects every new incoming flow towards the controller. In the data plane, we assigned a signature-based intrusion detection system to inspect traffic between Open Flow switches using port mirroring to analyse and detect malicious activity. Our flow-based system works with the help of trained, multi-layer machine learning-based classifier, while our signature-based system works with rule-based classifiers using the Snort intrusion detection system. The ensemble feature selection technique we adopted in the flow-based system helps to identify the prominent features and hasten the classification process. Our proposed work ensures a high level of security in the Software-defined networking environment by working simultaneously in both control plane and data plane.

Software defined networks (SDN) has gained a lot of attention from both academia and industry recently. SDN is a new networking paradigm that decouples the control plane from the data plane. In this paradigm, control functions are centralized in an SDN controller. The migration from traditional networks to SDN is highly challenging for network operators. Sudden migration may not be possible due to the cost and operational issues. Therefore, incremental deployment of SDN is considered as a viable solution, resulting in the formation of hybrid SDN networks. An important task in hybrid SDN networks is bandwidth allocation and routing considering the coexistence of both conventional and SDN-enabled routers. In this paper, we first formulate this problem as a multi-objective integer program with delay and capacity constraints. Then, a heuristic approach is proposed to combat the computational complexity of the model. Our proposed method is extensively analyzed through simulations, and the evaluation results confirm the effectiveness of our approach.

The traditional network architecture cannot meet the growing needs of increasingly diverse network applications. The new generation network architectures, software defined network (SDN) which have features of high openness, flexibility, scalability and high controllability have widely been studied. However, a series of new problems are also produced in this new architecture, such as security problem resulted from the high openness, and performance problem resulted from the high flexibility. Currently, the researchers are mainly concentrated in the implementation and standardisation of SDN. There is no good approach to evaluate and optimise the system performance. This studies the performance problems unresolved in SDN research area, and proposed an idea and method to analyse the control channel of ForCES (Forwarding and Control Element Separation)‐based SDN by using the stochastic network calculus theory. First, the architecture of ForCES‐based SDN is introduced. Then, the performance model of the channel is given. Based on the model, an optimisation method to performance is detailed. This study also gives a simulation by using NS‐2 (Network Simulator, Version 2) to verify the correctness and reliability of the performance model.

Current research in data dissemination in Vehicular Ad Hoc Networks (VANETs) has examined different approaches and frameworks to enhance the effectiveness and dependability of information sharing between vehicles on the road. The integration of Machine Learning (ML) with Software-Defined Networking (SDN) has fundamentally transformed the field of network administration and security. This paper specifically addresses the challenges faced by traditional network architectures in effectively handling the increasing amount of data and complex applications. Software-Defined Networking (SDN), a cutting-edge framework, separates the control of network operations from the actual forwarding of data, offering a versatile and cost-effective solution. The combination of Software-Defined Networking (SDN) and Machine Learning (ML) allows for the extraction of valuable information from network data, leading to enhanced network management and the facilitation of predictive analytics. The aim of this study is to examine the feasibility and challenges of incorporating machine learning into software-defined networking (SDN), focusing particularly on practical applications. Integrating Machine Learning (ML) into Software-Defined Networking (SDN) presents challenges, including the requirement for robust algorithms to detect patterns and ensure security. It is crucial to carry out the tasks of developing and implementing machine learning models for real-time predictions and ensuring the robustness of the system. Research is essential to strike a balance between the transformative abilities of ML-SDN and the practical network environments. This helps to improve the resilience, security, and adaptability of network infrastructures in the digital age.

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.

The exponential growth in the number of devices connected via the internet has led to the need to achieve granular programmability for increased performance, resilience, reduced latency, and jitter. Software Defined Networking (SDN) and Programming Protocol independent Packet Processing (P4) are designed to introduce programmability into the control and data plane of networks, respectively. Despite their individual potential and capabilities, the performance of combining SDN and P4 remains underexplored. This study presents a comprehensive evaluation of SDN with data plane programmability using P4 (SDN+P4) against traditional SDN with Open vSwitch (SDN+OvS), aimed at answering the hypothesis that combining SDN and P4 strengthens the control and data plane programmability and offers improved management and adaptability, which would provide a platform with faster packet processing with reduced jitter, loss, and processing overhead. Mininet was employed to emulate three distinct topologies: multi-path, grid, and transit-stub. Various traffic types were transmitted to assess performance metrics across the three topologies. Our results demonstrate that SDN+P4 outperform SDN+OvS significantly due to parallel processing, flexible parsing, and reduced overhead. The evaluation demonstrates the potential of SDN+P4 to provide a more resilient and stringent service with improved network performance for the future internet and its heterogeneity of applications.

Software defined networking (SDN) reshapes the ossified network architectures, by decoupling the control plane and data plane. Due to such a decoupling, SDN assumes that rules issued by the control plane are always correctly enforced by the data plane. However, this assumption breaks as an adversary can prevent the data plane from enforcing the rules, by exploiting the vulnerabilities of switch OS and control channel. The serious consequence is that packets may deviate from their original paths, thereby violating critical security policies like access control. To this end, this paper introduces rule enforcement verification (REV) , which enables the controller to check whether switches have correctly enforced the rules that it issues. Since using message authentication code (MAC) can incur heavy switch-to-controller traffic, we propose the compressive MAC , which lets switches compress MACs before reporting to the controller, thereby significantly reducing the bandwidth cost. Finally, we propose a heuristic flow selection algorithm, which allows the controller to verify much less flows for rule coverage. We implement REV based on Open vSwitch with DPDK, and use experiments to show: (1) by using compressive MAC, REV achieves a 97% reduction in switch-to-controller traffic, and an $8\times $ increase in verification throughput; (2) by using the heuristic flow selection algorithm, REV can reduce the number of flows to verify by 40%–60%.

Anonymous communication technology has been proposed to conceal the identity and communication relationship of both parties in communication, mitigating the threats of communication surveillance. However, the traditional anonymous communication scheme is designed on the traditional network architecture, network devices have limited control over the network, which leads to the inefficiency of anonymous communication. Software Defined Networks (SDN) is a novel network architecture that manages network through controller. It has the characteristics of high efficiency and flexibility. However, in recent years, researches about anonymous communication of SDN exist many challenges, such as limitation of scenarios and lack of anonymity. To address these challenges, this paper, inspired by pseudonym changing, proposes a pseudonym-based anonymous routing mechanism under multi-controller SDN architecture, in which pseudonym-changing is used for hiding the identity of the communicating parties. Besides, to avoid routing error caused by address conflicts, an effective hash checking method is proposed to avoid anonymous address conflicts. Based on that, we also present an anonymity enhanced scheme that employs phantom routing to hide the sender in the routing path and a multicast mechanism to prevent traffic analysis attacks. Anonymity analysis and experiment show that this scheme can provide strong anonymity protection for distributed SDN without much time cost, and has good practicability.

Software-Defined Networking (SDN) architecture was developed to address the shortcomings of traditional network architectures. It allows system administrators to easily manage and configure the network by separating and abstracting the control plane from the data plane. All the knowledge and intelligence of SDN is concentrated in a software entity called the SDN controller, making the network programmable. However, a large-scale SDN architecture, particularly in the IoT domain, requires the implementation of a physically distributed control mechanism. Such a mechanism, based on the East/West interface raises many challenges in terms of scalability, reliability, security, consistency, and traceability. The development of the Blockchain allows addressing some of these challenges. In this paper, we present a design using Blockchain technology to improve SDNs in terms of trackability and discuss the adaptations required for large-scale deployment. Experimental results clearly show that the use of a proof-of-authority consensus algorithm in combination with a Merkle tree approach reduces the impact in terms of latency as well as in terms of Gas consumption.

Failures are inevitable in an operational network. They can happen anytime in different sizes and components of a network. They impact the network economics regarding CAPEX (Capital Expenditure), OPEX (Operational Expenditure), revenue lost due to service provisioning cut and so on. In order to mitigate the damages resulting from these failures, reactions of network architectures and designs are crucial for the future of the network. Recently, Software Defined Networking (SDN) has got the attention of researchers from both academia and industry as a means in order to increase network availability and reliability due to features, such as centralized automated control and global network view, it promises in networking. To this end, we explore the effects of programmable network architectures, i.e. SDN technology, and traditional network architectures, i.e. MPLS (Multiprotocol Label Switching) technology, on network economics by exploiting Number of Satisfied Service Requests and our predefined Unit Service Cost Scalability metrics under network failure scenarios: i) a random single data plane link failure and ii) a random controller (i.e. control plane) failure. To the best of our knowledge, this study is the first to consider a comparison of a programmable network architecture, i.e. SDN, along with different control plane models, Centralized (Single) Control Plane (CCP), Distributed (Flat) Control Plane (DCP), and Hierarchical Control Plane (HCP), and a non-programmable network architecture, i.e. MPLS, regarding network economics in case of network failures.

As the traditional network architecture can not meet the requirements of network users for high-quality network services, software defined network (SDN) has been proposed as a new network architecture. SDN divides the data plane and control plane in the network equipment, so that the controller can schedule the data in the network flexibly through openflow protocol. Floodlight and Ryu are two typical SDN controllers proposed for different purposes. In this paper, we first introduce Floodlight and Ryu, and then introduce the tools used in the paper: mininet and qperf. Then, we simulate the two controllers of Floodlight and Ryu, and compare their bandwidth and delay performance under different network topologies. The experimental results show that in all kinds of topology, the Floodlight controller has higher bandwidth and lower latency than Ryu controller, so the Floodlight controller has better performance.