Emerging Trends and Challenges in Fog and Edge Computing for the Internet of Things

A special issue of IoT (ISSN 2624-831X).

Deadline for manuscript submissions: closed (1 October 2021) | Viewed by 20789

Special Issue Editors


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Guest Editor
University of Nantes/LS2N lab, 44306 Nantes, France
Interests: computer networks; Internet of Things; LPWAN; fog/edge computing; wireless sensors networks; mobile ad hoc networks; networks of robots

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Guest Editor
Inatysco SAS, 34000 Montpellier, France
Interests: distributed storage; fog/edge computing; network protocols; blockchain; p2p networks

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) requires a deep reorganization of the infrastructure to support acceptable Quality of Service (QoS). For 10 years, new paradigms have been proposed to realise a continuum between the Clouds and the IoT: the fog and edge computing. The goal of this new architecture is to plunge all the numerous tiny connected devices in near distributed resources that provide computing and storing capabilities. But the Internet was not designed for this usage at the origin. In this context we can enumerate different ongoing problems like internetworking and interoperability, how to store data and to perform distributed computation, or how to support mobility, scalability, availability, security in this infrastructure which has energy constraints.

This special issue addresses all those problems with encouraging emerging technologies from networks and distributed systems communities. In particular, we can note (but not limited to) the interesting information centric approaches (Named Data Networking, Information Centric Networking,...) or new adapted propositions for IoT in Peer-to-Peer (P2P) networks and distributed ledgers like blockchains.

Those systems are by definition complex to configure and monitor. To cope with this issue machine learning can provide auto-configuration, self-organisation and auto-diagnosis. Authors are so invited to share their experiences to apply deep learning, data mining, and reinforcement learning in fog and edge computing for the IoT.

Finally, very large scale experiments from the sensors to the clouds constitute a real challenge to validate protocols, architectures, systems, software programs and middlewares. We expect contributions in this area with special attention on open sources/open hardware and reproducibility. In vivo experiments and real deployments are also more than welcome to illustrate concretely this special issue in various domains like Industrie 4.0, environmental and wildlife monitoring, health, energy, telecommunications, multimedia.

To sum up, the topics are (but not limited to):

  • QoS in Fog/Edge computing for the IoT
  • Interoperability in Fog/Edge computing for the IoT
  • Distributed storage in Fog/Edge computing for the IoT
  • Security (threats detection, authentication, permission management) in Fog/Edge computing for the IoT
  • Energy and sustainability in Fog/Edge computing for the IoT
  • Service location protocols in Fog/Edge environments for the IoT
  • Information Centric Networks (ICN) and Named Data Networking (NDN) in Fog/Edge computing for the IoT
  • P2P networks and blockchains in Fog/Edge computing for the IoT
  • Auto-configuration, self-organisation or server selection protocols in Fog/Edge computing for the IoT
  • Auto-diagnosis in Fog/Edge computing for the IoT
  • Deep Learning, Reinforcement Learning, Federated Learning in Fog/Edge computing for the IoT
  • Large scale experiments in Fog/Edge computing for the IoT
  • Applications of Fog/Edge computing for the IoT in Industry 4.0, ecosystem monitoring, health, energy, telecommunications, multimedia

Dr. Benoît Parrein
Dr. Bastien Confais
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. IoT is an international peer-reviewed open access quarterly 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 1200 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 (5 papers)

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Editorial

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2 pages, 149 KiB  
Editorial
Emerging Trends and Challenges in Fog and Edge Computing for the Internet of Things
by Bastien Confais and Benoît Parrein
IoT 2022, 3(1), 145-146; https://doi.org/10.3390/iot3010009 - 16 Feb 2022
Cited by 1 | Viewed by 3091
Abstract
Current network architectures such as Cloud computing are not adapted to provide an acceptable Quality of Service (QoS) to the large number of tiny devices that compose the Internet of Things (IoT) [...] Full article

Research

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23 pages, 4354 KiB  
Article
BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems
by Oluwashina Joseph Ajayi, Joseph Rafferty, Jose Santos, Matias Garcia-Constantino and Zhan Cui
IoT 2021, 2(4), 610-632; https://doi.org/10.3390/iot2040031 - 14 Oct 2021
Cited by 7 | Viewed by 5057
Abstract
The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, [...] Read more.
The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency response, and advanced computation, among others. However, in contrast with the benefits offered by edge computing capabilities, there are several detractors, such as centralized data storage, data ownership, privacy, data auditability, and security, which concern the IoT community. This study leveraged blockchain’s inherent capabilities, including distributed storage system, non-repudiation, privacy, security, and immutability, to provide a novel, advanced edge computing architecture for IoT systems. Specifically, this blockchain-based edge computing architecture addressed centralized data storage, data auditability, privacy, data ownership, and security. Following implementation, the performance of this solution was evaluated to quantify performance in terms of response time and resource utilization. The results show the viability of the proposed and implemented architecture, characterized by improved privacy, device data ownership, security, and data auditability while implementing decentralized storage. Full article
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25 pages, 5278 KiB  
Article
A Pervasive Collaborative Architectural Model at the Network’s Periphery
by Ghassan Fadlallah, Hamid Mcheick and Djamal Rebaine
IoT 2021, 2(3), 524-548; https://doi.org/10.3390/iot2030027 - 6 Sep 2021
Cited by 2 | Viewed by 3610
Abstract
Pervasive collaborative computing within the Internet of Things (IoT) has progressed rapidly over the last decade. Nevertheless, emerging architectural models and their applications still suffer from limited capacity in areas like power, efficient computing, memory, connectivity, latency and bandwidth. Technological development is still [...] Read more.
Pervasive collaborative computing within the Internet of Things (IoT) has progressed rapidly over the last decade. Nevertheless, emerging architectural models and their applications still suffer from limited capacity in areas like power, efficient computing, memory, connectivity, latency and bandwidth. Technological development is still in progress in the fields of hardware, software and wireless communications. Their communication is usually done via the Internet and wireless via base stations. However, these models are sometimes subject to connectivity failures and limited coverage. The models that incorporate devices with peer-to-peer (P2P) communication technologies are of great importance, especially in harsh environments. Nevertheless, their power-limited devices are randomly distributed on the periphery where their availability can be limited and arbitrary. Despite these limitations, their capabilities and efficiency are constantly increasing. Accelerating development in these areas can be achieved by improving architectures and technologies of pervasive collaborative computing, which refers to the collaboration of mobile and embedded computing devices. To enhance mobile collaborative computing, especially in the models acting at the network’s periphery, we are interested in modernizing and strengthening connectivity using wireless technologies and P2P communication. Therefore, the main goal of this paper is to enhance and maintain connectivity and improve the performance of these pervasive systems while performing the required and expected services in a challenging environment. This is especially important in catastrophic situations and harsh environments, where connectivity is used to facilitate and enhance rescue operations. Thus, we have established a resilient mobile collaborative architectural model comprising a peripheral autonomous network of pervasive devices that considers the constraints of these resources. By maintaining the connectivity of its devices, this model can operate independently of wireless base stations by taking advantage of emerging P2P connection technologies such as Wi-Fi Direct and those enabled by LoPy4 from Pycom such as LoRa, BLE, Sigfox, Wi-Fi, Radio Wi-Fi and Bluetooth. Likewise, we have designed four algorithms to construct a group of devices, calculate their scores, select a group manager, and exchange inter- and intra-group messages. The experimental study we conducted shows that this model continues to perform efficiently, even in circumstances like the breakdown of wireless connectivity due to an extreme event or congestion from connecting a huge number of devices. Full article
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18 pages, 935 KiB  
Article
Analysis of P4 and XDP for IoT Programmability in 6G and Beyond
by David Carrascal, Elisa Rojas, Joaquin Alvarez-Horcajo, Diego Lopez-Pajares and Isaías Martínez-Yelmo
IoT 2020, 1(2), 605-622; https://doi.org/10.3390/iot1020031 - 15 Dec 2020
Cited by 8 | Viewed by 4570
Abstract
Recently, two technologies have emerged to provide advanced programmability in Software-Defined Networking (SDN) environments, namely P4 and XDP. At the same time, the Internet of Things (IoT) represents a pillar of future 6G networks, which will be also sustained by SDN. In this [...] Read more.
Recently, two technologies have emerged to provide advanced programmability in Software-Defined Networking (SDN) environments, namely P4 and XDP. At the same time, the Internet of Things (IoT) represents a pillar of future 6G networks, which will be also sustained by SDN. In this regard, there is a need to analyze the suitability of P4 and XDP for IoT. In this article, we aim to compare both technologies to help future research efforts in the field. For this purpose, we evaluate both technologies by implementing diverse use cases, assessing their performance and providing a quick qualitative overview. All tests and design scenarios are publicly available in GitHub to guarantee replication and serve as initial steps for researchers that want to initiate in the field. Results illustrate that currently XDP is the best option for constrained IoT devices, showing lower latency times, half the CPU usage, and reduced memory in comparison with P4. However, development of P4 programs is more straightforward and the amount of code lines is more similar regardless of the scenario. Additionally, P4 has a lot of potential in IoT if a special effort is made to improve the most common software target, BMv2. Full article
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Review

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15 pages, 2519 KiB  
Review
Bibliometric Analysis of Scientific Productivity around Edge Computing and the Internet of Things
by Antonio-José Moreno-Guerrero, Francisco-Javier Hinojo-Lucena, Magdalena Ramos Navas-Parejo and Gerardo Gómez-García
IoT 2020, 1(2), 436-450; https://doi.org/10.3390/iot1020024 - 17 Nov 2020
Cited by 4 | Viewed by 3331
Abstract
Technological progress has recently led to the emergence of various technological resources and means that are improving specific aspects of society. An example of this can be found in the “internet of things” and “edge computing”. The present study aims at knowing and [...] Read more.
Technological progress has recently led to the emergence of various technological resources and means that are improving specific aspects of society. An example of this can be found in the “internet of things” and “edge computing”. The present study aims at knowing and analyzing the scientific literature of the set of terms formed by “edge computing” and “internet of things”, called from now on ECIT. In order to carry out the research, a study has been developed, based on bibliometrics, by means of scientific mapping. In this case, different production indicators have been taken into account, as well as the structural and dynamic development of the terms and authors extracted from the publications through the programs Analyze Results, Creation Citation Report and SciMAT. The results indicate that the study theme “edge computing” and “internet of things” is of recent creation, given that its beginnings date back to 2014. Since then the level of production has been dizzying, increasing considerably in the past two years. It can be concluded that the field of study of ECIT is of recent creation, with a solid research base based on the “internet of things”. Furthermore, the themes “big data”, “energy” and “framework” can be considered as the future lines of research on ECIT. Full article
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