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Electronics
Special Issues
Applications of Software Defined Networking
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Applications of Software Defined Networking

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

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 11101

Special Issue Editor

Dr. Habib Mostafaei

E-Mail Website
Guest Editor
Technische Universität Berlin, 10623 Berlin, Germany
Interests: software-defined networking (SDN); network measurements; distributed systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Software-defined networking (SDN) offers numerous advantages to network operators and service providers, as well as data center providers. With SDN, the network infrastructure is more dynamic, programmable, and is capable of controlling the underlying infrastructure components. SDN has brought with it many benefits, such as reduced costs, better scalability, flexibility, manageability, and fine-grained control of traffic. This happens through programming the network forwarding behavior through the control plane interface using the controller.

 The main objective of this Special Issue is to focus on the recent applications of SDN in the various domains of wired and wireless networks. Potential topics include, but are not limited to, the following:

  • SDN applications in network monitoring
  • SDN applications in security services
  • SDN applications in routing
  • SDN applications in distributed application control
  • SDN applications in resource management
  • SDN applications in cloud networking
  • SDN applications in the Internet of Things
  • SDN applications in wireless sensor networks

Dr. Habib Mostafaei
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.

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

Published Papers (1 paper)

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28 pages, 722 KiB  
Review
A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges
by Imran, Zeba Ghaffar, Abdullah Alshahrani, Muhammad Fayaz, Ahmed Mohammed Alghamdi and Jeonghwan Gwak
Electronics 2021, 10(8), 880; https://doi.org/10.3390/electronics10080880 - 7 Apr 2021
Cited by 63 | Viewed by 9826
Abstract
In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of [...] Read more.
In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of data. One major contribution to the research world is in the form of software-defined networking applications, which aim to deploy rule-based management to control and add intelligence to the network using high-level policies to have integral control of the network without knowing issues related to low-level configurations. Machine learning techniques coupled with software-defined networking can make the networking decision more intelligent and robust. The Internet of Things application has recently adopted virtualization of resources and network control with software-defined networking policies to make the traffic more controlled and maintainable. However, the requirements of software-defined networking and the Internet of Things must be aligned to make the adaptations possible. This paper aims to discuss the possible ways to make software-defined networking enabled Internet of Things application and discusses the challenges solved using the Internet of Things leveraging the software-defined network. We provide a topical survey of the application and impact of software-defined networking on the Internet of things networks. We also study the impact of machine learning techniques applied to software-defined networking and its application perspective. The study is carried out from the different perspectives of software-based Internet of Things networks, including wide-area networks, edge networks, and access networks. Machine learning techniques are presented from the perspective of network resources management, security, classification of traffic, quality of experience, and quality of service prediction. Finally, we discuss challenges and issues in adopting machine learning and software-defined networking for the Internet of Things applications. Full article
(This article belongs to the Special Issue Applications of Software Defined Networking)
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