An Energy-Efficient Branch and Bound Optimization Algorithm for Large-Scale Software-Defined Networks

In today's ever-evolving networking landscape, Software Defined Networking (SDN) has emerged as a paradigm-shifting technology that promises greater flexibility, agility, and control over network infrastructures. However, how easy are the configuration, extensibility, and programmability of these SDN controllers, considering the practical implications for network administrators and developers? Despite the growing adoption of SDN, there is limited research on the comparative performance of controllers across multiple simulation environments. This study aims to explore the practical implementation and comparative evaluation of different SDN Controllers within diverse simulated network environments. Prominent controllers such as POX and Faucet are meticulously configured and deployed in simulated network environments created using GNS3 (Graphical Network Simulator-3), OPNET (Optimized Network Engineering Tools), NS3 (Network Simulator-3), OMNET++ (Objective Modular Network Testbed in C++) and MININET platforms. Furthermore. the study employs a range of performance metrics like controller latency, network throughput, packet loss, CPU (Central Processing Unit) and memory utilization to assess the efficacy and efficiency of each SDN Controller. The Results indicated that Mininet provided the lowest latency, whereas OPNET demonstrated better scalability for large-scale networks. NS3, though useful for SDN network design and visualization, exhibited higher CPU and memory utilization that might limit its scalability for large-scale SDN controller simulations. While GNS3 offered a balanced performance and resource utilization, making it a suitable choice for SDN controller simulation that prioritizes realistic network modelling, OMNET++, on the other hand, exhibited moderate performance metrics with efficient resource utilization, making it suitable for SDN controller simulations requiring a balance between performance...

Considering the problem that the SDN controller can not fully resolve the virtual network function during the Software Defined Network (SDN) and Network Function Virtualization (NVF) collaborative deployment in the satellite network, a SDN/NFV coordination based on the three-layer satellite network is designed. The framework extends the SDN controller function and proposes the SDN controller function extension method (SDN-FE) based on LightGBM algorithm. SDN-FE has extended the functions of the original SDN controller in three aspects. One is based on LightGBM to establish a classification model for intelligent forwarding of SDN controller data packets. The second is to learn and predict VNF modification of data packets through logistic regression. The third is to design an idle state monitoring mechanism. The above method effectively enhances the control capability of the SDN controller to the network. In terms of SDN packet forwarding classification, SDN-FE is compared with existing well-known machine learning classification algorithms such as SVM, random forest, LSTM. Simulation experiments show that the SDN packet forwarding classification problem is predictable. The average accuracy of the LightGBM model in multi-classification problems is over 69%, which is better than machine learning models such as SVM and random forest. The next step is to conduct an in-depth study of the packet rule learning algorithm in VNF.

Software-Defined Networking (SDN) revolutionizes network management by decoupling control plane functionality from data plane devices, enabling the centralized control and programmability of network behavior. This paper uses the ternary system to improve the Central Processing Unit (CPU) inside the SDN controller to enhance network management. The Multiple-Valued Logic (MVL) circuit shows remarkable improvement compared to the binary circuit regarding the chip area, propagation delay, and energy consumption. Moreover, the Carbon Nanotube Field-Effect Transistor (CNTFET) shows improvement compared to other transistor technologies regarding energy efficiency and circuit speed. To the best of our knowledge, this is the first time that a ternary design has been applied inside the CPU of an SDN controller. Earlier studies focused on Ternary Content-Addressable Memory (TCAM) in SDN. This paper proposes a new 1-trit Ternary Full Adder (TFA) to decrease the propagation delay and the Power-Delay Product (PDP). The proposed design is compared to the latest 17 designs, including 15 designs that are 1-trit TFA CNTFET-based, 2-bit binary FA FinFET-based, and 2-bit binary FA CMOS-based, using the HSPICE simulator, to optimize the CPU utilization in SDN environments, thereby enhancing programmability. The results show the success of the proposed design in reducing the propagation delays by over 99% compared to the 2-bit binary FA CMOS-based design, over 78% compared to the 2-bit binary FA FinFET-based design, over 91% compared to the worst-case TFA, and over 49% compared to the best-case TFAs.

Intent-Based Networking (IBN) is an emerging networking paradigm while Moving Target Defense (MTD) is an active security technique. In this paper, the Intent-based Moving Target Defense (INMTD) framework using Software Defined Networks is proposed. INMTD is the first effort in exploiting IBN for the design of an efficient Moving Target Defense (MTD) framework. INMTD uses the concept of shadow servers in order to counter the first stage of cyber-attacks, i.e. reconnaissance attacks targeted against servers running in SDN networks. INMTD comprises of an MTD application running on an SDN controller. The MTD application has reconnaissance detection, MTD movement, and MTD monitoring modules. The MTD application is integrated with the intent-based northbound API of SDN controller. INMTD not only provides protection against probing attacks, but it also provides high availability due to shadow servers. The proposed framework was implemented using Mininet and ONOS SDN controller. The proposed framework was assessed in terms of defender cost, attacker’s effort, and introduced complexity in the system. The results substantiate the efficient protection against reconnaissance attacks at lower computational cost.

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.

Software Defined Network (SDN) Technology made tremendous changes in networking field by controlling the hardware with remote software by decoupling data plane and control plane. The focus here is on the controller which is part of control plane. A controller is a central part of SDN; it is an intermediary between Data plane and Forwarding plane. It takes prime place in SDN architecture like Operating System in Computers. SDN Controller is a software which directs the packets using flow rules and also contains statistical information of network. The controller orchestrates the networking devices such as switches and routers by channelizing the packets. SDN controller has different flavor based on the commercial requirement achieved by including new pluggable module. This paper discusses some of the SDN Controller with their feature; the controllers are POX, NOX, Floodlight, ODL, Open Contrail. This paper also compares the characteristic of centralized and distributed controller by focusing on performance, bandwidth and round-trip time of Floodlight and Open Daylight (ODL) controller. The simulation is conducted using Mininet.

Software defined networks (SDN) remain a hot research field as it provides controllable networking operations. The SDN controller can be treated as the operating system of the SDN model and it holds the responsibility of performing different networking applications. Despite the benefits of SDN, security remains a challenging problem. At the same time, distributed denial of services (DDoS) is a typical attack on SDN owing to centralized architecture, especially at the control layer of the SDN. This article develops a new Cat Swarm Optimization with Fuzzy Rule Base Classification (CSO-FRBCC) model for cybersecurity in SDN. The presented CSO-FRBCC model intends to effectually categorize the occurrence of DDoS attacks in SDN. To achieve this, the CSO-FRBCC model primarily pre-processes the input data to transform it to a uniform format. Besides, the CSO-FRBCC model employs FRBCC classifier for the recognition and classification of intrusions. Moreover, the parameter optimization of the FRBCC classification model is adjusted by the use of cat swarm optimization (CSO) algorithm which results in improved performance. A comprehensive set of simulations were carried out on benchmark dataset and the results highlighted the enhanced outcomes of the CSO-FRBCC model over the other recent approaches.

Software-Defined Networking (SDN) is now a well-established approach in 5G, Internet of Things (IoT) and Cloud Computing. The primary idea behind its immense popularity is the separation of its underlying intelligence from the data-carrying components like routers and switches. The intelligence of the SDN-based networks lies in the central point, popularly known as the SDN controller. It is the central control hub of the SDN-based network, which has full privileges and a global view over the entire network. Providing security to SDN controllers is one such important task. Whenever one wishes to implement SDN into their data center or network, they are required to provide the website to SDN controllers. Several attacks are becoming a hurdle in the exponential growth of SDN, and among all one such attack is a Distributed Denial of Service (DDoS) attack. In a couple of years, several new SDN controllers will be available. Among many, Open Networking Operating System (ONOS) and OpenDayLight (ODL) are two popular SDN controllers laying the foundation for many other controllers. These SDN controllers are now being used by numerous businesses, including Cisco, Juniper, IBM, Google, etc. In this paper, vulnerability analysis is carried out against DDoS attacks on the latest released versions of both ODL and ONOS SDN controllers in real-time cloud data centers. For this, we have considered distributed SDN controllers (located at different locations) on two different clouds (AWS and Azure). These controllers are connected through the Internet and work on different networks. DDoS attacks are bombarded on the distributed SDN controllers, and vulnerability is analyzed. It was observed with experimentation that, under five different scenarios (malicious traffic generated), ODL-3 node cluster controller had performed better than ONOS. In these five different scenarios, the amount of malicious traffic was incregradually increased. It also observed that, in terms of disk utilization, memory utilization, and CPU utilization, the ODL 3-node cluster was way ahead of the SDN controller.

Interest in OpenFlow and software-defined network (SDNs) has resulted in a boom in SDN hardware and controller offerings, with varying degrees of maturity, popularity and support. However, few studies have been conducted to investigate the interaction between SDN hardware and software, as well as its impact on controller design and implementation. In this paper, we chronicle our experience with deploying two commodity SDN controllers and a new system, IronStack, of our own design in a production enterprise network at Cornell University, and describe the lessons learnt. We also report on several practical limitations of SDN and controller technology, and detail important future challenges for SDN adopters and developers.

Unmanned aerial vehicles that abbreviates (UAVs) are flying platforms, known as drones, which have features such as mobility, adaptive altitude and flexibility. UAVs admit numerous applications that can be used as aerial base stations to enhance coverage, capacity, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. A Software Defined Network (SDN) Controller is the application that acts as a strategic control point in a software-defined network. It is the ’brain’ of the network. Controller manages flow control to the routers/switches ‘under’ (via southbound APIs), the business logic and applications ’above’ (via northbound APIs) to deploy intelligent networks. Wireless networking with software defined (SDWN) is the use of SDN conceptions in wireless networks by using a controller in the control plane. SDWN facilitates the creation of new adaptive mechanisms according to various applications and user requirements, such as mobility, handover, security and quality of service (QoS). In this paper, simulation work has been conducted to compare and investigate four SDN controllers (Pox, Ryu, Floodlight and OpenDaylight) in order to see which one is suitable to be used. Mininet-Wifi has been selected as the simulation tool to do the experiments and Python script for programming. The results obtained reveals that Ryu controller is the best selection in terms of latency and packet loss.

Software defined networking (SDN) is the centralised network management technology that could reduce the network administration and policy enforcement overhead in the traditional IP networking. SDN controller is the network operating system responsible for entire network operations. However, there are many open source controllers available, such as NOX, POX, FloodLight and OpenDaylight. Each controller has its own properties that could support specific requirements. In this paper, we have compared the performance of most familiar OpenFlow controllers like NOX, POX, Ryu, FloodLight and OpenFlow reference controller based on their packet handling capacity, by varying the packet size, number of packets and arrival pattern in the IP traffic flows. Distributed internet traffic flow generator (D-ITG) tool has been used to measure the performance in terms of delay, jitter, throughput and packet loss. Our experimentation results show that, FloodLight has the better throughput and less delay when compared to other controllers. This work substantiates the researcher in choosing the appropriate controller for their requirements.

Wireless Sensor Networks (WSNs) have a wide range of applications scenarios in computer vision, from pedestrian detection to robotic visual navigation. In response to the growing visual data services in WSNs, we propose a proactive caching strategy based on Stacked Sparse Autoencoder (SSAE) to predict content popularity (PCDS2AW). Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. Then, the SSAE network structure parameters and network model parameters are optimized through training. The proactive cache strategy implementation procedure is divided into four steps. (1) The SDN controller is responsible for dynamically collecting user request data package information in the WSNs network. (2) The SSAEs predicts the packet popularity based on the SDN controller obtaining user request data. (3) The SDN controller generates a corresponding proactive cache strategy according to the popularity prediction result. (4) Implement the proactive caching strategy at the WSNs cache node. In the simulation, we compare the influence of spatiotemporal data on the SSAE network structure. Compared with the classic caching strategy Hash + LRU, Betw + LRU, and classic prediction algorithms SVM and BPNN, the proposed PCDS2AW proactive caching strategy can significantly improve WSN performance.

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.

Software Defined Networking (SDN) is a rapidly emerging technology in the commercial market, and is a technology that should be embraced by the defence and emergency services to enable more flexible and adaptable communication networks in the future. Common deployment of SDN, especially in data centres, involves building a separate network for the control channel between forwarding devices and the SDN controllers. For geographically distributed networks typically found in defence and emergency services, it is often not feasible to establish a separate dedicated network for the control channel. In such networks, traffic between SDN controllers and forwarding devices therefore needs to be in-band in the same network that the SDN controllers should control. This paper describes the steps necessary for forwarding devices to both discover and set up the connections with SDN controllers when in-band control channels must be used. The work expands on earlier published work on setting up in-band control channels between SDN controllers and the forwarding devices. Especially, our solution that uses the Intent frameworks of major SDN controllers improves on network resilience in disconnected, intermittent and limited networks and the solution will allow for implementation of enhanced security mechanisms compared to previous work.

In this era wireless technology gaining more popularity, people prefer wireless communication over wired communication due to mobility, scalability and ease of access. However, the traditional wireless network is complex, vendor dependent and inadequate feasibility to incorporate new services, protocols, and APIs. The rapid growth in wireless network raises many thoughtful challenges for network and telecom operators. On such grounds, Innovation of Software Defined Network (SDN) and network function virtualization (NFV) for mobile network opens a new arena of research. This research article presents future mobile Internet architecture (FMIA) with the integration of twin technologies, SDN and NFV that enable rapid access to Internet services. Moreover, the network manager can control services provided by ISPs through proposed architecture.