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Applied Sciences
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Software Defined Networks in IoT Environments
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Software Defined Networks in IoT Environments

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 12625

Special Issue Editors

Dr. Miguel García-Pineda

E-Mail Website
Guest Editor
Computer Science Department, University of Valencia, 46100 Valencia, Spain
Interests: multimedia networks; streaming; QoE; QoS; IoTs; cloud computing
Special Issues, Collections and Topics in MDPI journals
Dr. Jaume Segura-Garcia

E-Mail Website
Guest Editor
Department of Computer Science, ETSE, Universitat de València, 46100 Burjassot, Valencia, Spain
Interests: IoT; WSN; Smart Cities; signal processing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

As we know, the number of devices connected to the internet is growing exponentially, creating the IoT (Internet of Things). As a result, we have heterogeneous networks where their management, control, and monitoring tend to be complex according to the traditional network infrastructure. For this reason, we have to create new network infrastructures to improve their operation by providing intelligence, efficiency, security, and scalability. On the other hand, software-defined networks are characterized by separating the control plane from the data plane, where control tasks are performed by a controller that communicates with the devices through the OpenFlow protocol. This operation allows the network administrator to have a global vision of the network and to control or manage the traffic according to the needs of each moment.

Therefore, the union between IoT and SDN technologies can contribute to the reduction of several disadvantages in the IoT’s implementation. SDN brings an improvement in the management and control of the network due to its architecture being more flexible and scalable. This Special Issue on “Software-Defined Networks in IoT environments” aims to reflect recent developments in software-defined networks in IoT and to present new advances in software-defined networks that enable the development of future IoT networks. Submissions are expected to focus on theoretical aspects and applications of software-defined networks in IoT environments. New ideas proposing disruptive approaches are also welcome.

Topics of interest include but are not limited to the following areas:

  • Software-defined network (SDN) architectures and design in IoT;
  • Network function virtualization (NFV) architectures and design in IoT;
  • Hardware system design for SDN-NFV in IoT;
  • SDN-powered mobile edge computing;
  • Softwarization of IoT devices;
  • IoT-enabling technologies;
  • IoT security with SDN;
  • Edge and fog computing in IoT;
  • Case studies in IoT–SDN.

We hope this Special Issue works as a roadmap for all researchers of SDN in IoT environments.

Dr. Miguel García-Pineda
Dr. Jaume Segura-Garcia
Guest Editors

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. Applied Sciences 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.

Published Papers (4 papers)

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Research

10 pages, 1035 KiB  
Article
Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things
by Jesus Lopez-Ballester, Jose M. Alcaraz Calero, Jaume Segura-Garcia, Santiago Felici-Castell, Miguel Garcia-Pineda and Maximo Cobos
Appl. Sci. 2021, 11(4), 1430; https://doi.org/10.3390/app11041430 - 05 Feb 2021
Cited by 3 | Viewed by 2546
Abstract
In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, [...] Read more.
In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, we study the application of a WASN for room acoustic measurements. To evaluate the acoustic characteristics, a set of Raspberry Pi 3 (RPi) has been used. One is used to play different acoustic signals and four are used to record at different points in the room simultaneously. The signals are sent wirelessly to a computer connected to a server, where using MATLAB we calculate both the impulse response (IR), and different acoustic parameters, such as the Speech Intelligibility Index (SII). In this way, the evaluation of room acoustic parameters with asynchronous IR measurements two different applications has been explored. Finally, the network features have been evaluated to assess the effectiveness of this system. Full article
(This article belongs to the Special Issue Software Defined Networks in IoT Environments)
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27 pages, 1697 KiB  
Article
Mitigating DDoS Attacks in SDN-Based IoT Networks Leveraging Secure Control and Data Plane Algorithm
by Song Wang, Karina Gomez, Kandeepan Sithamparanathan, Muhammad Rizwan Asghar, Giovanni Russello and Paul Zanna
Appl. Sci. 2021, 11(3), 929; https://doi.org/10.3390/app11030929 - 20 Jan 2021
Cited by 23 | Viewed by 3521
Abstract
Software-Defined Networking (SDN) and Internet of Things (IoT) are the trends of network evolution. SDN mainly focuses on the upper level control and management of networks, while IoT aims to bring devices together to enable sharing and monitoring of real-time behaviours through network [...] Read more.
Software-Defined Networking (SDN) and Internet of Things (IoT) are the trends of network evolution. SDN mainly focuses on the upper level control and management of networks, while IoT aims to bring devices together to enable sharing and monitoring of real-time behaviours through network connectivity. On the one hand, IoT enables us to gather status of devices and networks and to control them remotely. On the other hand, the rapidly growing number of devices challenges the management at the access and backbone layer and raises security concerns of network attacks, such as Distributed Denial of Service (DDoS). The combination of SDN and IoT leads to a promising approach that could alleviate the management issue. Indeed, the flexibility and programmability of SDN could help in simplifying the network setup. However, there is a need to make a security enhancement in the SDN-based IoT network for mitigating attacks involving IoT devices. In this article, we discuss and analyse state-of-the-art DDoS attacks under SDN-based IoT scenarios. Furthermore, we verify our SDN sEcure COntrol and Data plane (SECOD) algorithm to resist DDoS attacks on the real SDN-based IoT testbed. Our results demonstrate that DDoS attacks in the SDN-based IoT network are easier to detect than in the traditional network due to IoT traffic predictability. We observed that random traffic (UDP or TCP) is more affected during DDoS attacks. Our results also show that the probability of a controller becoming halt is 10%, while the probability of a switch getting unresponsive is 40%. Full article
(This article belongs to the Special Issue Software Defined Networks in IoT Environments)
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17 pages, 1083 KiB  
Article
SDN-Based Control of IoT Network by Brain-Inspired Bayesian Attractor Model and Network Slicing
by Onur Alparslan, Shin’ichi Arakawa and Masayuki Murata
Appl. Sci. 2020, 10(17), 5773; https://doi.org/10.3390/app10175773 - 20 Aug 2020
Cited by 2 | Viewed by 2250
Abstract
One of the models in the literature for modeling the behavior of the brain is the Bayesian attractor model, which is a kind of machine-learning algorithm. According to this model, the brain assigns stochastic variables to possible decisions (attractors) and chooses one of [...] Read more.
One of the models in the literature for modeling the behavior of the brain is the Bayesian attractor model, which is a kind of machine-learning algorithm. According to this model, the brain assigns stochastic variables to possible decisions (attractors) and chooses one of them when enough evidence is collected from sensory systems to achieve a confidence level high enough to make a decision. In this paper, we introduce a software defined networking (SDN) application based on a brain-inspired Bayesian attractor model for identification of the current traffic pattern for the supervision and automation of Internet of things (IoT) networks that exhibit a limited number of traffic patterns. In a real SDN testbed, we demonstrate that our SDN application can identify the traffic patterns using a limited set of fluctuating network statistics of edge link utilization. Moreover, we show that our application can improve core link utilization and the power efficiency of IoT networks by immediately applying a pre-calculated network configuration optimized by traffic engineering with network slicing for the identified pattern. Full article
(This article belongs to the Special Issue Software Defined Networks in IoT Environments)
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21 pages, 1280 KiB  
Article
Enforcing Behavioral Profiles through Software-Defined Networks in the Industrial Internet of Things
by Sara Nieves Matheu García, Alejandro Molina Zarca, José Luis Hernández-Ramos, Jorge Bernal Bernabé and Antonio Skarmeta Gómez
Appl. Sci. 2019, 9(21), 4576; https://doi.org/10.3390/app9214576 - 28 Oct 2019
Cited by 14 | Viewed by 3585
Abstract
The fourth industrial revolution is being mainly driven by the integration of Internet of Things (IoT) technologies to support the development lifecycle of systems and products. Despite the well-known advantages for the industry, an increasingly pervasive industrial ecosystem could make such devices an [...] Read more.
The fourth industrial revolution is being mainly driven by the integration of Internet of Things (IoT) technologies to support the development lifecycle of systems and products. Despite the well-known advantages for the industry, an increasingly pervasive industrial ecosystem could make such devices an attractive target for potential attackers. Recently, the Manufacturer Usage Description (MUD) standard enables manufacturers to specify the intended use of their devices, thereby restricting the attack surface of a certain system. In this direction, we propose a mechanism to manage securely the obtaining and enforcement of MUD policies through the use of a Software-Defined Network (SDN) architecture. We analyze the applicability and advantages of the use of MUD in industrial environments based on our proposed solution, and provide an exhaustive performance evaluation of the required processes. Full article
(This article belongs to the Special Issue Software Defined Networks in IoT Environments)
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