Software Defined Networking Implementation Research Articles

Implementation of automation configuration of enterprise networks as software defined network

Software defined network (SDN) is a new computer network configuration concept in which the data plane and control plane are separated. In Cisco system, the SDN concept is implemented in Cisco Application Centric Infrastructure (Cisco ACI), which by default can be configured through the main controller, namely the Application Policy Infrastructure Controller (APIC). Conventional configuration on Cisco ACI creates problems, i.e.: the large number of required configurations causes the increase of time required for configuration and the risk of misconfiguration due to repetitive works. This problem reduces the productivity of network engineers in managing Cisco system. In overcoming these problems, this research work proposes an automation tool for Cisco ACI configuration using Ansible and Python as an SDN implementation for optimizing enterprise network configuration. The SDN is implemented and experimented at PT. NTT Indonesia Technology network, as a case study. The experimental result shows the proposed SDN successfully performs multiple routers configurations accurately and automatically. Observations on manual configuration takes 50 minutes and automatic configuration takes 6 minutes, thus, the proposed SDN achieves 833.33% improvement.

Implementation of automation configuration of enterprise networks as software defined network

Software defined network (SDN) is a new computer network configuration concept in which the data plane and control plane are separated. In Cisco system, the SDN concept is implemented in Cisco Application Centric Infrastructure (Cisco ACI), which by default can be configured through the main controller, namely the Application Policy Infrastructure Controller (APIC). Conventional configuration on Cisco ACI creates problems, i.e.: the large number of required configurations causes the increase of time required for configuration and the risk of misconfiguration due to repetitive works. This problem reduces the productivity of network engineers in managing Cisco system. In overcoming these problems, this research work proposes an automation tool for Cisco ACI configuration using Ansible and Python as an SDN implementation for optimizing enterprise network configuration. The SDN is implemented and experimented at PT. NTT Indonesia Technology network, as a case study. The experimental result shows the proposed SDN successfully performs multiple routers configurations accurately and automatically. Observations on manual configuration takes 50 minutes and automatic configuration takes 6 minutes, thus, the proposed SDN achieves 833.33% improvement.

Machine-Learning-Based Traffic Classification in Software-Defined Networks

Many research efforts have gone into upgrading antiquated communication network infrastructures with better ones to support contemporary services and applications. Smart networks can adapt to new technologies and traffic trends on their own. Software-defined networking (SDN) separates the control plane from the data plane and runs programs in one place, changing network management. New technologies like SDN and machine learning (ML) could improve network performance and QoS. This paper presents a comprehensive research study on integrating SDN with ML to improve network performance and quality-of-service (QoS). The study primarily investigates ML classification methods, highlighting their significance in the context of traffic classification (TC). Additionally, traditional methods are discussed to clarify the ML outperformance observed throughout our investigation, underscoring the superiority of ML algorithms in SDN TC. The study describes how labeled traffic data can be used to train ML models for appropriately classifying SDN TC flows. It examines the pros and downsides of dynamic and adaptive TC using ML algorithms. The research also examines how ML may improve SDN security. It explores using ML for anomaly detection, intrusion detection, and attack mitigation in SDN networks, stressing the proactive threat-detection and response benefits. Finally, we discuss the SDN-ML QoS integration problems and research gaps. Furthermore, scalability and performance issues in large-scale SDN implementations are identified as potential issues and areas for additional research.

Enhancing QoS of Telecom Networks through Server Load Management in Software-Defined Networking (SDN)

In the modern era, with the emergence of the Internet of Things (IoT), big data applications, cloud computing, and the ever-increasing demand for high-speed internet with the aid of upgraded telecom network resources, users now require virtualization of the network for smart handling of modern-day challenges to obtain better services (in terms of security, reliability, scalability, etc.). These requirements can be fulfilled by using software-defined networking (SDN). This research article emphasizes one of the major aspects of the practical implementation of SDN to enhance the QoS of a virtual network through the load management of network servers. In an SDN-based network, several servers are available to fulfill users’ hypertext transfer protocol (HTTP) requests to ensure dynamic routing under the influence of the SDN controller. However, if the number of requests is directed to a specific server, the controller is bound to follow the user-programmed instructions, and the load on that server is increased, which results in (a) an increase in end-to-end user delay, (b) a decrease in the data transfer rate, and (c) a decrease in the available bandwidth of the targeted server. All of the above-mentioned factors will result in the degradation of network QoS. With the implementation of the proposed algorithm, dynamic active sensing server load management (DASLM), on the SDN controller, the load on the server is shared based on QoS control parameters (throughput, response time, round trip time, etc.). The overall delay is reduced, and the bandwidth utilization along with throughput is also increased.

Controller placement problem during SDN deployment in the ISP/Telco networks: A survey

AbstractWith the successful implementation of Software‐Defined Networking (SDN) in data center networking, the way forward for its deployment in the ISP/Telco network is becoming prominent. Small and medium‐sized networks may easily adopt SDN. The research on SDN deployment and implementation for a large‐scale network is continuing. This paper properly presents the current research status of Controller Placement Problem (CPP) and Multi‐CPP (MCPP) over SDN with their specific challenges and provides a comprehensive review of the major performance metrics, that is, latency, and controller load balancing techniques. This survey highlights the use of network partitioning‐based CPP and clustering approaches and their benefits in the context of SDN deployment. Moreover, this paper highlights the importance of implementing SDN and SDN security issues into ISP/Telco networks. Finally, we provide some key areas of ongoing research and discuss the future research direction regarding the various SDN‐based Controller Placement (CP) issues in the next‐generation IP and advanced networking technologies.

A Review on Utilizing Big Data Techniques for Performance Improvement in Software Defined Networking

Traditional network abilities have a drastic shortage in the current networking world. Software-Defined Networking (SDN) is a revival development in the networking domain that provides separation of control and data planes, enlarges the data plane granularity, and simplifies the network devices. All these factors accelerate and automate the evolution of new services. However, when the SDN network topology becomes large, it poses new challenges in security, traffic management, and scalability due to the vast amounts of traffic data generated and the need for additional controllers to manage the significant number of networking devices. On the other hand, big data has become an attractive trend that can enhance network performance in general, specifically SDN. Both SDN and big data have gained great attraction from industry and academia. Traditionally, these two subjects have been studied separately in most of the preceding works. However, big data can impact the design and implementation of SDN thoroughly. This paper presents how big data can support SDN in various aspects, including intrusion detection, traffic monitoring, and controller scalability and resiliency. We suggest several approaches toward deeper cooperation between big data and SDN. Index Term – SDN, big data, Spark, graph database, traffic engineering, intrusion detection.

Enabling Efficient IoT Device Connectivity and Dynamic Network Management through SDN: A Weighted Sum Method Approach

SDN-Enabled IoT Networks bring about a transformative shift in conventional network models by integrating the core principles of Software-Defined Networking (SDN) into the realm of the Internet of Things (IoT). This integration empowers the agile and effective management of IoT devices, facilitating smooth connectivity, optimized distribution of resources, and flexible network setups. Through the consolidation of control and the utilization of virtualization methods, SDN-Enabled IoT Networks amplify scalability, security, and real-time responsiveness. This addresses the obstacles presented by the extensive proliferation of IoT devices. This paradigm transition heralds a fresh era of interconnectedness, where SDN assumes a central role in harmonizing the intricate interplay of IoT devices and services. The rapid expansion of Internet of Things (IoT) devices has introduced unparalleled complexities in overseeing networks and establishing connections. This compels the need for inventive strategies to effectively manage the substantial surge of IoT devices and their ever-changing connectivity prerequisites. Software-Defined Networking (SDN) emerges as a promising approach to tackle these issues by enabling the flexible management of networks and allocation of resources. This study investigates the amalgamation of SDN within the realm of IoT, aiming to streamline device connections, optimize data transmission efficiency, and accommodate adaptable network setups. Introducing an innovative weighted sum technique for resource allocation optimization, this work lays the foundation for a comprehensive framework that bolsters IoT network performance and expandability. Four different SDN implementations are examined, including the Conventional IoT Network, SDN-enabled IoT utilizing Centralized Control, SDN-enabled IoT employing Distributed Control, SDN-enabled IoT with Hierarchical Control, and SDN-enabled IoT utilizing Hybrid Control. The assessment considers various aspects such as Enhanced Scalability, Enhanced Traffic Engineering, Heightened Security, Implementation Complexity, Difficulty of Migration, and Reliance on Vendors. The Conventional IoT Network secures a moderate 3rd position with a Preference Score of 0.56030, while the SDN-enabled IoT with Centralized Control holds the 5th rank at 0.49732, despite excelling in specific domains. The SDN-enabled IoT with Distributed Control achieves the top rank with a notable Preference Score of 0.79414 due to comprehensive performance, followed by the SDN-enabled IoT with Hierarchical Control securing the 2nd spot (Preference Score: 0.57022), and the SDN-enabled IoT with Hybrid Control taking the 4th position (Preference Score: 0.51300), particularly excelling in Traffic Engineering.

Enhancing the security of Software-Defined Networks (SDNs)

Software-defined networking (SDN) is an emerging paradigm, which breaks the vertical integration in traditional networks to provide the flexibility to program the network through (logical) centralized network control. SDN has the capability to adapt its network parameters on the fly based on its operating environment. The decoupled structure of SDN serves as a solution for managing the network with more flexibility and ease. In SDN, the centralized cost effective architecture provides network visibility which helps to achieve efficient resource utilization and high performance. Due to the increasingly pervasive existence of smart programmable devices in the network, SDN provides security, and network virtualization for enhancing the overall network performance. The work presents various security threats that are resolved by SDN and new threats that arise as a result of SDN implementation. The recent security attacks and countermeasures in SDN are also summarized in the form of tables. Also provided a survey on the different strategies that are implemented to achieve energy efficiency and network security through SDN implementation. In an effort to anticipate the future evolution of this new paradigm, were discussed the main ongoing research efforts, challenges, and research trends in this area. With this work, researchers and students can have a more thorough understanding of SDN architecture, different security attacks and countermeasures.

Software Defined Network Implementation by Using OpenDayLight Centralized Controller

The most attractive study framework among academics is Software Define Networking Networking SDN, which aims to create the Internet with an architecture-independent architecture that will lead to the most significant advances in the network field. This can solve many network problems to deal with high demand changes and reduce Replenishment, changes and less manual work. Because of the limited architecture of traditional networks, which requires modifications in the basic design, network expansion has been mature and slow. Since 2010, until now, the ODL - OpenDayLight model has been proposed to solve most of the problems that guide network engineers in the process of managing complex high-volume networks by top research-oriented universities around the world. Now is the time to turn dreams into reality by putting the presented ideas into action, which will result in a solution that meets the expectations of the researcher regarding the process of managing complex networks and all forms of networks. This document is an attempt to assist researchers in implementing a software identification network infrastructure on which the research community may focus on further analysis and development. We demonstrated an incremental approach to implementing ODL - OpenDayLight Controller (ODL is a JVM program and can run from any operating system and device as long as it supports Java) from the Software Define Network, as well as creating and executing required scenarios, and illustrate the working nature of ODL - OpenDayLight compared to ryu contrlloer, in this paper Research. Index Terms— SDN, OpenDayLight, Mininet, Switch, Controller, Performance evaluation.

Towards a blockchain-SDN-based secure architecture for cloud computing in smart industrial IoT

Some of the significant new technologies researched in recent studies include BlockChain (BC), Software Defined Networking (SDN), and Smart Industrial Internet of Things (IIoT). All three technologies provide data integrity, confidentiality, and integrity in their respective use cases (especially in industrial fields). Additionally, cloud computing has been in use for several years now. Confidential information is exchanged with cloud infrastructure to provide clients with access to distant resources, such as computing and storage activities in the IIoT. There are also significant security risks, concerns, and difficulties associated with cloud computing. To address these challenges, we propose merging BC and SDN into a cloud computing platform for the IIoT. This paper introduces “DistB-SDCloud”, an architecture for enhanced cloud security for smart IIoT applications. The proposed architecture uses a distributed BC method to provide security, secrecy, privacy, and integrity while remaining flexible and scalable. Customers in the industrial sector benefit from the dispersed or decentralized, and efficient environment of BC. Additionally, we described an SDN method to improve the durability, stability, and load balancing of cloud infrastructure. The efficacy of our SDN and BC-based implementation was experimentally tested by using various parameters including throughput, packet analysis, response time, bandwidth, and latency analysis, as well as the monitoring of several attacks on the system itself.

A Scalable Framework to Detect, Analyze, and Prevent Security Vulner abilities in Enterprise Software-Defined Networks

Software Defined Networking (SDN) is a rapidly growing technology that is enabling innovation on how network systems are designed and managed. Like any other technology, SDN is susceptible to numerous security threats. The separation of planes and centralized control topology of SDN makes it vulnerable to myriad of attacks. There has been rapid implementation of SDN in variety of networks and this is only growing with time. There are only handful of resources for enterprise networks that are actively transitioning their networks to SDN and require security specification.This paper proposes a security framework that integrates basic security requirements for SDN. First, the security vulnerabilities are identified by assessing the SDN topology. This provides understanding of the issue which is utilized to implement security mechanisms that help mitigate the vulnerabilities. The framework utilizes open-source tools and techniques and integrates well-known security mechanisms. Throughout the paper, the proposed framework is implemented and tested for its success in satisfying some of the basic and crucial security requirements. In doing so, this research offers viable security mechanisms for enterprise networks that are looking for performance and cost-effective security solutions.

Simulation of 5G Mobile Core Network using SDN & MPLS

In particular, in order to have the best possible understanding of the effects that program-able networking has, carry out a low cost analysis of both the (software define network) system and the (multiple protocol layer switching)  system. This will give you the possible understanding of the effects that program-able networking has on the economics of a network in comparison to traditional networking, which is also known as MPLS technology. This is done so that a better understanding of the effects that program-able networking, also known as software-defined networking (SDN), technology has on the economics of a network can be gained. Conducting a quantitative investigation using an activity-based methodology to compute the (capital expenditure) and (operation expenditure) costs associated with a network was the first step in achieving this objective. This investigation was carried out.  Second, in order to compare the aforementioned architectures in terms of their financial performances, we used the USC Scalability metric in addition to the Cost-to-Service metric. Both of these metrics were used. These models include (centralized control plane), (distributed control plane), and (hierarchical control plane). This was done in order to obtain the possible understanding of the different SDN plane systems that are currently in use. The separation of control plane and data plane that is achieved through the implementation of software-defined networking (SDN) makes it possible to program networks. Because of this separation, network operators and administrators are now in a position to make better use of the network's resources and have an easier time provisioning those resources when compared to the situation before the separation took place.

FybrrLink: Efficient QoS-Aware Routing in SDN Enabled Future Satellite Networks

Providing high-speed Internet services using satellite networks have attracted researchers from both academia and industry mainly due to the characteristics of Low Earth Orbit (LEO) satellite networks such as global coverage, scalability, and lower transmission delays. Implementation of Software-Defined Networking (SDN) in Non-Terrestrial Networks (NTNs) can help to achieve the goals set for 5G and beyond networks. Since satellite networks have a specific architecture, some of the legacy protocols no longer remain useful. Therefore, to satisfy the diverse Quality of Service (QoS) requirements for a variety of applications, we propose a novel and centralized QoS-aware routing algorithm, called fybrrLink in which the global view of the network in SDN is utilized. We implement a modified Bresenham’s algorithm and Dijkstra’s algorithm to find the optimal path in a significantly reduced computation time. Also, taking advantage of the deterministic satellite constellation, we propose a flow rule transfer algorithm and a topology monitoring algorithm. Further, fybrrLink is evaluated with multiple NS3 simulations, and results confirm that our approach outperforms other state-of-the-art algorithms.

Software-Defined Networking: Categories, Analysis, and Future Directions.

Software-defined networking (SDN) is an innovative network architecture that splits the control and management planes from the data plane. It helps in simplifying network manageability and programmability, along with several other benefits. Due to the programmability features, SDN is gaining popularity in both academia and industry. However, this emerging paradigm has been facing diverse kinds of challenges during the SDN implementation process and with respect to adoption of existing technologies. This paper evaluates several existing approaches in SDN and compares and analyzes the findings. The paper is organized into seven categories, namely network testing and verification, flow rule installation mechanisms, network security and management issues related to SDN implementation, memory management studies, SDN simulators and emulators, SDN programming languages, and SDN controller platforms. Each category has significance in the implementation of SDN networks. During the implementation process, network testing and verification is very important to avoid packet violations and network inefficiencies. Similarly, consistent flow rule installation, especially in the case of policy change at the controller, needs to be carefully implemented. Effective network security and memory management, at both the network control and data planes, play a vital role in SDN. Furthermore, SDN simulation tools, controller platforms, and programming languages help academia and industry to implement and test their developed network applications. We also compare the existing SDN studies in detail in terms of classification and discuss their benefits and limitations. Finally, future research guidelines are provided, and the paper is concluded.

A comprehensive survey on software‐defined networking for smart communities

SummaryThe need to provide services closer to the end‐user proximity leads to the exchange of a large volume of data generated from the smart devices deployed at different geo‐distributed sites. The massive amount of data generated from the smart devices need to be transmitted, analyzed, and processed. This requires seamless data exchanges among geo‐separated nodes, which results in a considerable burden on the underlying network infrastructure and can degrade the performance of any implemented solution. Therefore, a dynamic, agile, and programmable network management paradigm is required. To handle the challenges mentioned above, software‐defined networking (SDN) gained much attention from academia, researchers, and industrial sectors. Shifting the computational load from forwarding devices to a logically centralized controller is a dream of every network operator who wants to have complete control and global visibility of the network. Also, the concept of network functions virtualization (NFV) in SDN controller is required to increase resource utilization efficiency. Thus, in this paper, a comprehensive survey on SDN for various smart applications is presented. This survey covers the infrastructural details of SDN hardware and OpenFlow switches, controllers, simulation tools, programming languages, open issues, and challenges in SDN implementation with advanced technologies such as 5G and microservices. In addition, the challenges on the control plane and data plane are highlighted in detail, such as fault tolerance, routing, scheduling of flows, and energy consumption on OpenFlow switches. Finally, various open issues and challenges future scope of SDN are discussed and analyzed in the proposal.

Enhancing Network Security through Software Defined Networking (SDN)

The IoT connects many of the home appliances in the world, from intelligent thermostats to intelligent vehicles. By the end of 2015, we had 9 billion connected stuff. The Gartner forecast shows that the number of devices in the network will exceed 50 billion by 2020. Most of the connected devices in the existing network are based on obsolete security infrastructure and encryption, while many do not have provisions for remote updating of these devices. Taking into account the number of IoT devices, from off-shelf motion monitoring to machine tools, it is not possible to check which functions end up with any specific service or product. In short, this is the problem: you can't trust the integrity of the security of the device and determine exactly where the data is processed and stored. The SDN architecture is designed to increase the routing and networking performance of the existing networks by isolating the control plane from the data plane. The basic concept of Software Defined Networking can be applied to IoT Multi networks; however, the standard SDN implementations for wired networks are not directly suitable for distributed and ad-hoc mesh networks, which are common in IoT systems. However, the SDN architecture changes the pattern of communication of the IoT network, leading to a new approach to the manifestation of the Securities IoT network. Centralized data layer control and control layer not only simplifies data package management, but also increases safety. As mentioned above, the amount of data that flows into these systems is significant. Proper management of traffic and load balancing will help to simplify the data flow in some ways. The total system's power consumption may be reduced by the central station, which requires less power than the distributed control. To sum up, introducing SDN into IoT will help IoT and stimulate IoT in people's regular lives.

Generic Method for SDN Controller Selection Using AHP and TOPSIS Methods

The control plane plays an essential role in the implementation of Software Defined Network (SDN) architecture. Basically, the control plane is an isolated process and operates on control layer. The control layer encompasses controllers which provide a global view of the entire SDN. The Controller selection is more crucial for the network administrator to meet the specific use case. This research work mainly focuses on obtaining a better SDN controller. Initially, the SDN controllers are selected using integrated Analytic Hierarchy Process and Technique for Order Preference Similarity to Ideal Solution (AHP and TOPSIS) method. It facilitates to select minimal number of controllers based on their features in the SDN application. Finally, the performance evaluation is carried out using the CBENCH tool considering the best four ranked controllers obtained from the previous step. In addition, it is validated with the real-time internet topology such as Abilene and ERNET considering the delay factor. The result shows that the “Floodlight” controller responds better for latency and throughput. The selection of an optimum controller-Floodlight, using the real-world Internet topologies, outperforms in obtaining the path with a 28.57% decrease in delay in Abilene and 16.94% in ERNET. The proposed work can be applied in high traffic SDN applications.

Optimized management of ultra-wideband photonics switching systems assisted by machine learning.

Recent years have seen an unprecedented growth of data traffic driven by a continuous increase of connected devices and new applications. This trend will tend to saturate transparent optical networks that are the backbone of the whole telecommunication infrastructure. To improve the capacity of already deployed network infrastructures and maximize operators CAPEX returns, band-division multiplexing (BDM) has emerged as a promising solution to expand the fiber bandwidth beyond the existing C-band. Along with this, the demand for flexible and dynamically reconfigurable functionalities in each network layer is increasing. In this regard, optical networking is fast evolving towards the applications of the software-defined networking (SDN) paradigm down to the physical layer. The implementation of optical SDN requires the full abstraction and virtualization of each network element in order to enable complete control by a centralized network controller. To pursue this objective, photonics transmission components and their transmission functionalities must be abstracted to allow the definition of the control states and a real-time quality-of-transmission (QoT) evaluation of transparent lightpaths (LP). In this work, we propose an SDN based model of a photonic switching fabric that allows determining the control state and evaluating QoT degradation. Our investigations present a wideband optical switch design based on photonic integrated circuits (PICs), where QoT degradation is abstracted using a structure-agnostic approach based on machine learning (ML). The ML engine training and testing datasets are generated synthetically by software simulation of the photonic switch architecture. Results show the potential of the proposed technique to predict QoT impairments with high accuracy, and we envision its application in a real-time control plane.

Enhanced Security of Software-defined Network and Network Slice Through Hybrid Quantum Key Distribution Protocol

Software-defined networking (SDN) has revolutionized the world of technology as networks have become more flexible, dynamic and programmable. The ability to conduct network slicing in 5G networks is one of the most crucial features of SDN implementation. Although network programming provides new security solutions of traditional networks, SDN and network slicing also have security issues, an important one being the weaknesses related to openflow channel between the data plane and controller as the network can be attacked via the openflow channel and exploit communications with the control plane. Our work proposes a solution to provide adequate security for openflow messages through using a hybrid key consisting of classical and quantum key distribution protocols to provide double security depending on the computational complexity and physical properties of quantum. To achieve this goal, the hybrid key used with transport layer security protocol to provide confidentiality, integrity and quantum authentication to secure openflow channel. We experimentally based on the SDN-testbed and network slicing to show the workflow of exchanging quantum and classical keys between the control plane and data plane and our results showed the effectiveness of the hybrid key to enhance the security of the transport layer security protocol. Thereby achieving adequate security for openflow channel against classical and quantum computer attacks.

Energy efficiency through joint routing and function placement in different modes of SDN/NFV networks

Network function virtualization (NFV) and software-defined networking (SDN) are two promising technologies to enable 5G and 6G services and achieve cost reduction, network scalability, and deployment flexibility. However, migration to full SDN/NFV networks in order to serve these services is a time-consuming process and costly for mobile operators. This paper focuses on energy efficiency during the transition of mobile core networks (MCN) to full SDN/NFV networks and explores how energy efficiency can be addressed during such migration. We propose a general system model containing a combination of legacy nodes and links, in addition to newly introduced NFV and SDN nodes. We refer to this system model as partial SDN and hybrid NFV MCN, which can cover different modes of SDN and NFV implementations. Based on this framework, we formulate energy efficiency by considering joint routing and function placement in the network. Since this problem belongs to the class of non-linear integer programming problems, to solve it efficiently, we present a modified Viterbi algorithm (MVA) based on multi-stage graph modeling and a modified Dijkstra’s algorithm. We simulate this algorithm for a number of network scenarios with different fractions of NFV and SDN nodes and evaluate how much energy can be saved through such transition. Simulation results confirm the expected performance of the algorithm, which saves up to 70% energy compared to a network where all nodes are always on. Interestingly, the amount of energy saved by the proposed algorithm in the case of hybrid NFV and partial SDN networks can reach up to 60%–90% of the saved energy in full NFV/SDN networks.