Advanced Internet of Things (IoT): Sensing Techniques, Hardware, and Software Architectures for the Next Generation Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 10161

Special Issue Editors


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Guest Editor
Department of Information Engineering, Universidad San Pablo-CEU, 28003 Madrid, Spain
Interests: IoT; energy harvesting and RF communication technologies; embedded AI; Edge and Cloud software and hardware architectures
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Engineering Sciences and Technology (INDI), Vrije Universiteit Brussel, 1050 Brussels, Belgium
Interests: IoT; reconfigurable computing; remote sensing; environmental monitoring; IoT for education; embedded energy harvesting
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Applied Physics, Universidad Autónoma de Madrid, 28049 Madrid, Spain
Interests: nanomaterials and nanodevices; optoelectronics; photonics

Special Issue Information

Dear Colleagues,

Internet of Things technologies are one of the major drivers of the technological transformation that we are experiencing in practically almost every sector of industry and economy, including smart cities, smart buildings, e-health, smart mobility, smart factories, smart appliances and even education.

The number of interconnected smart devices is increasing exponentially and, according to CISCO, there will be 500 billion interconnected devices by 2030.

This huge number of networked devices entails several design challenges throughout the entire IoT technological stack, including the cost of IoT enabled sensors, ecological impacts due to electronic waste, the exponential increase of data bandwidth requirements and high overall system latency due to the sensor-to-cloud paradigm, network security and data privacy.

In this Special Issue, we aim to collect high-quality submissions that target the most relevant practical engineering, and theoretical aspects behind the next-generation Internet of Things. The topics of interest include but are not limited to:

  • Smart sensing low-environmental impact materials for IoT.
  • Printable electronics for IoT.
  • Hybrid printable-silicon circuits for IoT.
  • Energy-scavenging techniques for IoT devices.
  • Low-power machine-to-machine protocols and wireless sensor networks.
  • Novel fog and edge architectures.
  • Embedded AI.
  • Novel security techniques for IoT and embedded devices.
  • Industrial IoT (IIoT).
  • Novel applications of IoT.
  • Embedded and IoT security.

Dr. Gianluca Cornetta
Dr. Abdellah Touhafi
Dr. Antonio Mariscal Jiménez
Guest Editors

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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

  • bidimensional materials
  • smart sensing materials
  • hybrid circuits
  • energy scavenging
  • machine to machine protocols
  • wireless sensor networks
  • embedded AI
  • embedded security
  • industrial IoT
  • edge architectures

Published Papers (5 papers)

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Research

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12 pages, 485 KiB  
Communication
A Streaming Data Processing Architecture Based on Lookup Tables
by Aximu Yuemaier, Xiaogang Chen, Xingyu Qian, Weibang Dai, Shunfen Li and Zhitang Song
Electronics 2023, 12(12), 2725; https://doi.org/10.3390/electronics12122725 - 19 Jun 2023
Viewed by 1103
Abstract
Processing in memory (PIM) is a new computing paradigm that stores the function values of some input modes in a lookup table (LUT) and retrieves their values when similar input modes are encountered (instead of performing online calculations), which is an effective way [...] Read more.
Processing in memory (PIM) is a new computing paradigm that stores the function values of some input modes in a lookup table (LUT) and retrieves their values when similar input modes are encountered (instead of performing online calculations), which is an effective way to save energy. In the era of the Internet of Things, the processing of massive data generated by the front-end requires low-power and real-time processing. This paper investigates an energy-efficient processing architecture based on table lookup in phase-change memory (PCM). This architecture replaces logical-based calculations with LUT lookups to minimize power consumption and operation latency. In order to improve the efficiency of table lookup, the RISC-V instruction set has included extended lookup and data stream transmission instructions. Finally, the system architecture is validated by hardware simulation, and the performance of computing the fast Fourier transform (FFT) application is evaluated. The proposed architecture effectively improves the execution efficiency and reduces the power consumption of data flow operations. Full article
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22 pages, 6207 KiB  
Article
Application and Research of IoT Architecture for End-Net-Cloud Edge Computing
by Yongqiang Zhang, Hongchang Yu, Wanzhen Zhou and Menghua Man
Electronics 2023, 12(1), 1; https://doi.org/10.3390/electronics12010001 - 20 Dec 2022
Cited by 11 | Viewed by 2855
Abstract
At the edge of the network close to the source of the data, edge computing deploys computing, storage and other capabilities to provide intelligent services in close proximity and offers low bandwidth consumption, low latency and high security. It satisfies the requirements of [...] Read more.
At the edge of the network close to the source of the data, edge computing deploys computing, storage and other capabilities to provide intelligent services in close proximity and offers low bandwidth consumption, low latency and high security. It satisfies the requirements of transmission bandwidth, real-time and security for Internet of Things (IoT) application scenarios. Based on the IoT architecture, an IoT edge computing (EC-IoT) reference architecture is proposed, which contained three layers: The end edge, the network edge and the cloud edge. Furthermore, the key technologies of the application of artificial intelligence (AI) technology in the EC-IoT reference architecture is analyzed. Platforms for different EC-IoT reference architecture edge locations are classified by comparing IoT edge computing platforms. On the basis of EC-IoT reference architecture, an industrial Internet of Things (IIoT) edge computing solution, an Internet of Vehicles (IoV) edge computing architecture and a reference architecture of the IoT edge gateway-based smart home are proposed. Finally, the trends and challenges of EC-IoT are examined, and the EC-IoT architecture will have very promising applications. Full article
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23 pages, 3718 KiB  
Article
PEASE: A PUF-Based Efficient Authentication and Session Establishment Protocol for Machine-to-Machine Communication in Industrial IoT
by Xiang Gong, Tao Feng and Maher Albettar
Electronics 2022, 11(23), 3920; https://doi.org/10.3390/electronics11233920 - 27 Nov 2022
Cited by 3 | Viewed by 1451
Abstract
Machine-to-machine (M2M) communication is one of the critical technologies of the industrial Internet of Things (IoT), which consists of sensors, actuators at the edge, and servers. In order to solve the security and availability problems regarding communication between edge devices with constrained resources [...] Read more.
Machine-to-machine (M2M) communication is one of the critical technologies of the industrial Internet of Things (IoT), which consists of sensors, actuators at the edge, and servers. In order to solve the security and availability problems regarding communication between edge devices with constrained resources and servers in M2M communication, in this study we proposed an authentication and session establishment protocol based on physical unclonable functions (PUFs). The scheme does not require clock synchronization among the devices, and it circumvents the situation where the authentication phase has to use a high computational overhead fuzzy extractor due to PUF noise. The protocol contains two message interactions, which provide strong security and availability while being lightweight. The security modelling is based on CPN Tools, which verifies security attributes and attack resistance in the authentication phase. After considering the design of the fuzzy extractor and scalability, the proposed scheme significantly reduces the computational overhead by more than 93.83% in the authentication phase compared with other schemes using PUFs. Meanwhile, under the guarantee of availability, the communication overhead is maintained at a balanced and reasonable level, at least 19.67% lower than the solution using XOR, hashing, or an elliptic curve. Full article
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22 pages, 947 KiB  
Article
Intelligent Replica Selection in Edge and IoT Environments Using Artificial Neural Networks
by Nour Mostafa, Wael Hosny Fouad Aly, Samer Alabed and Zakwan Al-Arnaout
Electronics 2022, 11(16), 2531; https://doi.org/10.3390/electronics11162531 - 13 Aug 2022
Cited by 4 | Viewed by 1265
Abstract
Cloud, edge and Internet of Things (IoT) technologies have emerged to overcome the challenges involved in sharing computational resources and information services. Within generic cloud systems, two models have been identified as having widespread applicability: computation clouds and data clouds. A data cloud [...] Read more.
Cloud, edge and Internet of Things (IoT) technologies have emerged to overcome the challenges involved in sharing computational resources and information services. Within generic cloud systems, two models have been identified as having widespread applicability: computation clouds and data clouds. A data cloud is cloud computing that aims to manage, unify and operate multiple data workloads. Many current applications generate datasets consisting of petabytes (PB) of information. Managing large datasets is a complex issuel; in particular, datasets associated with many applications can be distributed widely in geographical terms, particularly in IoT systems. Edge and IoT systems are facing new challenges with increased complexity, making scalability an important issue that will affect the performance of the system. Data replication services are widely accepted techniques to improve availability and fault tolerance, and to improve the data access time. Current replication services, however, often exhibit an increase in response time, reflecting the problems associated with the ever-increasing size of databases. This paper proposes a prediction model to predict replica locations using the files’ access profile, which feeds the neural networks with the access and location behavior (file profile) to minimize the overhead of transferring large volumes of data, which slows down the system and requires careful management. This new model has shown high accuracy and low overheads. The result shows a significant improvement in total task execution time using the proposed model for locating files by 16.34% and 30.45%; in addition, the results show bandwidth improvement by 24.7% and 49.4% compared to the user profile prediction model and replica service model without prediction, respectively. Consequently, the proposed algorithm can improve data access speed, reduce data access latency and decrease bandwidth consumption. Full article
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Review

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25 pages, 1959 KiB  
Review
An Overview of Technologies for Improving Storage Efficiency in Blockchain-Based IIoT Applications
by Nana Kwadwo Akrasi-Mensah, Eric Tutu Tchao, Axel Sikora, Andrew Selasi Agbemenu, Henry Nunoo-Mensah, Abdul-Rahman Ahmed, Dominik Welte and Eliel Keelson
Electronics 2022, 11(16), 2513; https://doi.org/10.3390/electronics11162513 - 11 Aug 2022
Cited by 6 | Viewed by 2647
Abstract
Since the inception of blockchain-based cryptocurrencies, researchers have been fascinated with the idea of integrating blockchain technology into other fields, such as health and manufacturing. Despite the benefits of blockchain, which include immutability, transparency, and traceability, certain issues that limit its integration with [...] Read more.
Since the inception of blockchain-based cryptocurrencies, researchers have been fascinated with the idea of integrating blockchain technology into other fields, such as health and manufacturing. Despite the benefits of blockchain, which include immutability, transparency, and traceability, certain issues that limit its integration with IIoT still linger. One of these prominent problems is the storage inefficiency of the blockchain. Due to the append-only nature of the blockchain, the growth of the blockchain ledger inevitably leads to high storage requirements for blockchain peers. This poses a challenge for its integration with the IIoT, where high volumes of data are generated at a relatively faster rate than in applications such as financial systems. Therefore, there is a need for blockchain architectures that deal effectively with the rapid growth of the blockchain ledger. This paper discusses the problem of storage inefficiency in existing blockchain systems, how this affects their scalability, and the challenges that this poses to their integration with IIoT. This paper explores existing solutions for improving the storage efficiency of blockchain–IIoT systems, classifying these proposed solutions according to their approaches and providing insight into their effectiveness through a detailed comparative analysis and examination of their long-term sustainability. Potential directions for future research on the enhancement of storage efficiency in blockchain–IIoT systems are also discussed. Full article
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