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Emerging Enabling Technologies for IoT
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Emerging Enabling Technologies for IoT

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 November 2018) | Viewed by 10843

Special Issue Editor

Dr. Davide Brunelli

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Trento, I-38123 Trento, Italy
Interests: energy harvesting; ultra-low-power sensors; IoT; energy-neutral devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to bring together members from different research communities and industrial practitioners to systematically explore the challenges, issues and opportunities in the research, design, and engineering of the Internet of Things (IoT). Wireless sensing devices, as well as edge/cloud frameworks, are the cornerstone for future IoT applications, and innovative solutions in device hardware, communication protocols, power management policies, sensor data fusion, cloud services and machine learning, are the ultimate frontiers.

High quality original technical articles are solicited, describing emerging enabling technologies for IoT, as well as those that describe practical deployments, implementation experiences and recent advances.

Authors are invited to submit contributions. Topics of interest for this Special Issue on “Emerging Enabling Technologies for IoT” include (but are not limited to):

  • Techniques for power management and energy harvesting for IoT devices
  • Heterogeneous, reconfigurable and other IoT-specific architectures
  • Industrial IoT sensors;
  • Wearable IoT;
  • Sensors Data Management;
  • IoT Localization Technologies;
  • Machine learning solutions for IoT applications
  • Advanced Computing architecture for smart IoT systems
  • Fog and Cloud Computing for IoT solutions

Dr. Davide Brunelli
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. Sensors 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 2600 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

  • IoT
  • power management
  • energy harvesting
  • sensor data fusion
  • fog computing
  • machine learning

Published Papers (3 papers)

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Research

22 pages, 3199 KiB  
Article
A Novel Synchronization Scheme Based on a Dynamic Superframe for an Industrial Internet of Things in Underground Mining
by Aiping Tan, Yuhuai Peng, Xianli Su, Haibin Tong and Qingxu Deng
Sensors 2019, 19(3), 504; https://0-doi-org.brum.beds.ac.uk/10.3390/s19030504 - 26 Jan 2019
Cited by 12 | Viewed by 4166
Abstract
The Industrial Internet of Things (IIoT) has a wide range of applications, such as intelligent manufacturing, production process optimization, production equipment monitoring, etc. Due to the complex circumstance in underground mining, the performance of WSNs faces enormous challenges, such as data transmission delay, [...] Read more.
The Industrial Internet of Things (IIoT) has a wide range of applications, such as intelligent manufacturing, production process optimization, production equipment monitoring, etc. Due to the complex circumstance in underground mining, the performance of WSNs faces enormous challenges, such as data transmission delay, packet loss rate, and so on. The MAC (Media Access Control) protocol based on TDMA (Time Division Multiple Access) is an effective solution, but it needs to ensure the clock synchronization between the transmission nodes. As the key technology of IIoT, synchronization needs to consider the factors of tunnel structure, energy consumption, etc. Traditional synchronization methods, such as TPSN (Timing-sync Protocol for Sensor Networks), RBS (Reference Broadcast Synchronization), mainly focus on improving synchronization accuracy, ignoring the impact of the actual environment, cannot be directly applied to the IIoT in underground mining. In underground mining, there are two kinds of nodes: base-station node and sensor node, which have different topologies, so they constitute a hybrid topology. In this paper, according to hybrid topology of unground mining, a clock synchronization scheme based on a dynamic superframe is designed. In this scheme, the base-station and sensor have different synchronization methods, improving the TPSN and RBS algorithm, respectively, and adjusts the period of the superframe dynamically by estimating the clock offset. The synchronization scheme presented in this paper can reduce the network communication overhead and energy consumption, ensuring the synchronization accuracy. Based on theCC2530 (Asystem-on-chip solution for IEEE 802.15.4, Zigbee and RF4CE applications), the experiments are compared and analyzed, including synchronization accuracy, energy consumption, and robustness tests. Experimental results show that the synchronization accuracy of the proposed method is at least 11% higher than that of the existing methods, and the energy consumption can be reduced by approximately 13%. At the same time, the proposed method has better robustness. Full article
(This article belongs to the Special Issue Emerging Enabling Technologies for IoT)
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19 pages, 1147 KiB  
Article
An Efficient Availability Guaranteed Deployment Scheme for IoT Service Chains over Fog-Core Cloud Networks
by Ngoc-Thanh Dinh and Younghan Kim
Sensors 2018, 18(11), 3970; https://0-doi-org.brum.beds.ac.uk/10.3390/s18113970 - 15 Nov 2018
Cited by 27 | Viewed by 3179
Abstract
High availability is one of the important requirements of many end-to-end services in the Internet of Things (IoT). This is a critical issue in network function virtualization (NFV) and NFV-enabled service function chaining (SFC) due to hard- and soft-ware failures. Thus, merely mapping [...] Read more.
High availability is one of the important requirements of many end-to-end services in the Internet of Things (IoT). This is a critical issue in network function virtualization (NFV) and NFV-enabled service function chaining (SFC) due to hard- and soft-ware failures. Thus, merely mapping primary VNFs is not enough to ensure high availability, especially for SFCs deployed over fog - core cloud networks due to resource limitations of fogs. As a result, additional protection schemes, like VNF redundancy deployments, are required to improve the availability of SFCs to meet predefined requirements. With limited resources of fog instances, a cost-efficient protection scheme is required. This paper proposes a cost-efficient availability guaranteed deployment scheme for IoT services over fog-core cloud networks based on measuring the improvement potential of VNFs for improving the availability of SFCs. In addition, various techniques for redundancy placement for VNFs at the fog layer are also presented. Obtained analysis and simulation results show that the proposed scheme achieves a significant improvement in terms of the cost efficiency and scalability compared to the state-of-the-art approaches. Full article
(This article belongs to the Special Issue Emerging Enabling Technologies for IoT)
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16 pages, 399 KiB  
Article
Torus Pairwise Disjoint-Path Routing
by Antoine Bossard and Keiichi Kaneko
Sensors 2018, 18(11), 3912; https://0-doi-org.brum.beds.ac.uk/10.3390/s18113912 - 13 Nov 2018
Cited by 2 | Viewed by 2467
Abstract
Modern supercomputers include hundreds of thousands of processors and they are thus massively parallel systems. The interconnection network of a system is in charge of mutually connecting these processors. Recently, the torus has become a very popular interconnection network topology. For example, the [...] Read more.
Modern supercomputers include hundreds of thousands of processors and they are thus massively parallel systems. The interconnection network of a system is in charge of mutually connecting these processors. Recently, the torus has become a very popular interconnection network topology. For example, the Fujitsu K, IBM Blue Gene/L, IBM Blue Gene/P, and Cray Titan supercomputers all rely on this topology. The pairwise disjoint-path routing problem in a torus network is addressed in this paper. This fundamental problem consists of the selection of mutually vertex disjoint paths between given vertex pairs. Proposing a solution to this problem has critical implications, such as increased system dependability and more efficient data transfers, and provides concrete implementation of green and sustainable computing as well as security, privacy, and trust, for instance, for the Internet of Things (IoT). Then, the correctness and complexities of the proposed routing algorithm are formally established. Precisely, in an n-dimensional k-ary torus ( n < k , k ≥ 5 ), the proposed algorithm connects c ( c ≤ n ) vertex pairs with mutually vertex-disjoint paths of lengths at most 2 k ( c − 1 ) + n ⌊ k / 2 ⌋ , and the worst-case time complexity of the algorithm is O ( n c 4 ) . Finally, empirical evaluation of the proposed algorithm is conducted in order to inspect its practical behavior. Full article
(This article belongs to the Special Issue Emerging Enabling Technologies for IoT)
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