Software-Defined Networks: Existing Approaches, Development and Challenges

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 7387

Special Issue Editor


E-Mail Website
Guest Editor
Department of AI Convergence & Electronic Engineering, Pukyong National University, Nam-gu, Busan 608737, Korea
Interests: vehicular network; edge/cloud computing; internet of things; software-defined network/virtualization

Special Issue Information

Dear Colleagues,

In recent years, software implementing networking functionality has become an emerging technology, which is gaining popularity among researchers. Software-defined networking (SDN) is an emerging network design and management paradigm that abstracts network information in a flexible way to tackle the complexity of traditional networks. In traditional network devices, roles are catalogued as independently working functional planes which interact with each other using  proprietary application programming interfaces (APIs). To address the issue of the rapid configuration of network devices, SDN defines a methodology where the control plane can be centralized with the purpose of gathering information from the network devices. These devices can perform pure forwarding plane functions and communicate with multiple data planes implemented by different vendors.

The promise of SDN is to create an infrastructure that is much more agile and flexible through ‘SDN automation’ to create programmable networks. With SDN automation, the goals of SDN are still being met by allowing the applications to influence forwarding decisions, and the APIs are available to build an application and use the APIs. This makes the network programmable, but not necessary flexible.

Regardless of which controllers and standard-based APIs (northbound) used, additional programmability of the network can enable better bandwidth utilization, improved application performance, and maximum operational efficiency.

Streaming telemetry is an approach for collecting data from network devices. Streaming telemetry pushes a stream of information from network devices, sending out to the necessary operational data center at the edge of the network or at a remote cloud data center. It may be programmed to send data periodically or based on specific events.

However, in-depth research efforts on systems, networks, and architectures of streaming telemetry for efficient large-scale collection are still being researched to fill the gaps between satisfying the quality of forwarding routing decisions and cost-effective SDN automation and operations.

The interaction of controllers from different vendors could enhance the separation between networking devices with the application of SDN. This helps in achieving exceptional flexibility in programmability and has enormous potential.

Thus, this Special Issue will present the researcher community with the latest research on existing approaches, developments and challenges in SDN as an emerging technology that addresses network automation by enabling new ways of network communications and services through evolving networking devices and systems with adaptive and scalable functionalities.

The aim of this Special Issue is to invite researchers to submit original manuscripts that cover and explore existing approaches, developments, and challenges in software-defined networking (SDN). This Special Issue solicits novel papers on a broad range of topics, including but not limited to:

Cutting-edge technologies, existing studies, and innovative developments that can realize and elevate the effectiveness and challenges of the emerging SDN-assisted technologies.

All papers submitted to this Special Issue should focus on state-of-the-art research in various aspects of smarter network systems and automation, supported with SDN, from academic and industry viewpoints. Topics of interest include, but are not limited to:

  • Architecture, networking protocols, QoS, and streaming-telemetry design;
  • Communication protocols for SDN—via overlays;
  • Communication protocols for SDN—via APIs;
  • Field trials and deployments of SDN—controllers;
  • SDN controllers based on cloud platforms and edge data centers;
  • Interworking of SDN with SDN protocols;
  • SDN architecture integration with artificial intelligence;
  • SDN-based automation over container orchestration platforms;
  • Security and performance of SDN for collecting network device information;
  • Traffic engineering and flow recovery in SDN;
  • Wireless-enabled intelligent transportation systems;
  • Streaming-efficient solutions for various problems, such as topology management, configuration scheduling, routing, and localization. 

Dr. Lionel Nkenyereye
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SDN
  • network systems
  • communication protocols
  • SDN automation
  • streaming telemetry

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 2556 KiB  
Article
Leveraging Software-Defined Networking for a QoS-Aware Mobility Architecture for Named Data Networking
by Muhammad Adnan, Jehad Ali, Manel Ayadi, Hela Elmannai, Latifa Almuqren and Rashid Amin
Electronics 2023, 12(8), 1914; https://doi.org/10.3390/electronics12081914 - 18 Apr 2023
Cited by 1 | Viewed by 1457
Abstract
The internet’s future architecture, known as Named Data Networking (NDN), is a creative way to offer content-based services. NDN is more appropriate for content distribution because of its special characteristics, such as naming conventions for packets and methods for in-network caching. Mobility is [...] Read more.
The internet’s future architecture, known as Named Data Networking (NDN), is a creative way to offer content-based services. NDN is more appropriate for content distribution because of its special characteristics, such as naming conventions for packets and methods for in-network caching. Mobility is one of the main study areas for this innovative internet architecture. The software-defined networking (SDN) method, which is employed to provide mobility management in NDN, is one of the feasible strategies. Decoupling the network control plane from the data plane creates an improved programmable platform and makes it possible for outside applications to specify how a network behaves. The SDN is a straightforward and scalable network due to its key characteristics, including programmability, flexibility, and decentralized control. To address the problem of consumer mobility, we proposed an efficient SDPCACM (software-defined proactive caching architecture for consumer mobility) in NDN that extends the SDN model to allow mobility control for the NDN architecture (NDNA), through which the MC (mobile consumer) receives the data proactively after handover while the MC is moving. When an MC is watching a real-time video in a state of mobility and changing their position from one attachment point to another, the controllers in the SDN preserve the network layout and topology as well as link metrics to transfer updated routes with the occurrence of the handoff or handover scenario, and through the proactive caching mechanism, the previous access router proactively sends the desired packets to the new connected routers. Furthermore, the intra-domain and inter-domain handover processing situations in the SDPCACM for NDNA are described here in detail. Moreover, we conduct a simulation of the proposed SDPCACM for NDN that offers an illustrative methodology and parameter configuration for virtual machines (VMs), OpenFlow switches, and an ODL controller. The simulation result demonstrates that the proposed scheme has significant improvements in terms of CPU usage, reduced delay time, jitter, throughput, and packet loss ratio. Full article
Show Figures

Figure 1

17 pages, 5764 KiB  
Article
Enhancing Software-Defined Networks with Intelligent Controllers to Improve First Packet Processing Period
by Ramesh Chand Meena, Surbhi Bhatia, Rutvij H. Jhaveri, Piyush Kumar Shukla, Ankit Kumar, Neeraj Varshney and Areej A. Malibari
Electronics 2023, 12(3), 600; https://doi.org/10.3390/electronics12030600 - 25 Jan 2023
Cited by 6 | Viewed by 1626
Abstract
Software-Defined Networking (SDN) has a detailed central model that separates the data plane from the control plane. The SDN controller is in charge of monitoring network security and controlling data flow. OpenFlow-enabled routers and switches work as packet-forwarding devices in the network system. [...] Read more.
Software-Defined Networking (SDN) has a detailed central model that separates the data plane from the control plane. The SDN controller is in charge of monitoring network security and controlling data flow. OpenFlow-enabled routers and switches work as packet-forwarding devices in the network system. At first, OpenFlow forwarding devices like routers and switches do not know how to handle the data packets transmitted by the host. This is because they do not have any security controls, policies, or information. These packets are sent to their destination. In this situation, the OpenFlow forwarding device sends the first data packet of a host to the SDN controller, which checks the control packets for the data packet and creates flow entries in the switch flow table to act on the following categories of data packets coming from the host. These activities at the SDN controller and switch levels are time-intensive, and the first data packet from the host always takes a longer time to reach its destination. In this article, we suggest an SDN controller with instant flow entries (SDN-CIFE) to reduce the amount of time it takes for the host to transmit its first data packet. Before traffic comes from the host, our method adds the necessary flow entries to the flow table of the OpenFlow switch. The technique was made in Python and tested on a Mininet network emulator using the RYU controller. The results of the experiment show that the time it takes to process the first data packet is reduced by more than 83%. Full article
Show Figures

Figure 1

17 pages, 858 KiB  
Article
Software-Defined Small Cell-Linked Vehicular Networks: Architecture and Evaluation
by Lionel Nkenyereye, Ramavath Prasad Naik, Jong-Wook Jang and Wan-Young Chung
Electronics 2023, 12(2), 304; https://doi.org/10.3390/electronics12020304 - 6 Jan 2023
Cited by 4 | Viewed by 1808
Abstract
Vehicle-to-everything services are in the implementation phase, and automakers agree that V2X would improve the safety-critical applications already deployed. 3GPP Release 12 introduces LTE-V for V2V and V2I services. The LTE-V is extended to C-V2X to support V2N. Because of the challenge of [...] Read more.
Vehicle-to-everything services are in the implementation phase, and automakers agree that V2X would improve the safety-critical applications already deployed. 3GPP Release 12 introduces LTE-V for V2V and V2I services. The LTE-V is extended to C-V2X to support V2N. Because of the challenge of high mobility in the V2X system, cutting-edge technologies, such as SDN and small cell in 5G networks, pave the way to the next generation of vehicular networks. SDN is a network technology concept that divides the data and control planes. The OpenFlow protocol is used for communication between the control layer and the network layer in SDN. Different from wireless traditional cellular base stations, small cells are lower-power cell sites that are deployed every few blocks. Small cells can transmit data using mid- and high-band spectrums. Small cell-linked road side unit (RSU) is considered a key enabling technology because it has the capability to create a logical cluster platform residing at the edge of the network, which provides high computation performance. Accordingly, we consider a novel distributed software-defined small cell-linked road side unit vehicular network architecture (diSRsVN). Based on diSRsVN, logical software-defined on-board wireless vehicle, and topology discovery over diSRsVN are presented. The proposed architecture is evaluated under an omnet++ network simulator. The simulation results show the effectiveness of the proposed architecture, which improves the packet delivery ratio and minimizes end-to-end delay. Full article
Show Figures

Figure 1

14 pages, 572 KiB  
Article
Improving the Energy Efficiency of Software-Defined Networks through the Prediction of Network Configurations
by Manuel Jiménez-Lázaro, Juan Luis Herrera, Javier Berrocal and Jaime Galán-Jiménez
Electronics 2022, 11(17), 2739; https://doi.org/10.3390/electronics11172739 - 31 Aug 2022
Cited by 5 | Viewed by 1606
Abstract
During the last years, huge efforts have been conducted to reduce the Information and Communication Technology (ICT) sector energy consumption due to its impact on the carbon footprint, in particular, the one coming from networking equipment. Although the irruption of programmable and softwarized [...] Read more.
During the last years, huge efforts have been conducted to reduce the Information and Communication Technology (ICT) sector energy consumption due to its impact on the carbon footprint, in particular, the one coming from networking equipment. Although the irruption of programmable and softwarized networks has opened new perspectives to improve the energy-efficient solutions already defined for traditional IP networks, the centralized control of the Software-Defined Networking (SDN) paradigm entails an increase in the time required to compute a change in the network configuration and the corresponding actions to be carried out (e.g., installing/removing rules, putting links to sleep, etc.). In this paper, a Machine Learning solution based on Logistic Regression is proposed to predict energy-efficient network configurations in SDN. This solution does not require executing optimal or heuristic solutions at the SDN controller, which otherwise would result in higher computation times. Experimental results over a realistic network topology show that our solution is able to predict network configurations with a high feasibility (>95%), hence improving the energy savings achieved by a benchmark heuristic based on Genetic Algorithms. Moreover, the time required for computation is reduced by a factor of more than 500,000 times. Full article
Show Figures

Figure 1

Back to TopTop