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Special Issue "IoT-Enabled Sensor Networks: Vision and Challenges"

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

Deadline for manuscript submissions: closed (15 October 2019).

Special Issue Editors

Prof. Dr. Antonio Puliafito
Website
Guest Editor
Department of Engineering, University of Messina, 98122 Messina, Italy
Interests: cloud; IoT; smart cities; embedded systems; cyberphysical systems
Special Issues and Collections in MDPI journals
Prof. Dr. Laurence T. Yang
Website
Guest Editor
Department of Computer Science, St. Francis Xavier University, Antigonish, Canada
Interests: parallel and distributed computing; embedded and ubiquitous/pervasive computing
Special Issues and Collections in MDPI journals
Dr. Giovanni Merlino
Website
Guest Editor
Department of Engineering, University of Messina, Contrada Di Dio, 98158 Sant'Agata, Messina ME, Italy
Interests: Cloud Computing; Internet of Things; Smart Sensors; Mobile Crowd Sensing; Software-Defined Networking

Special Issue Information

Dear Colleagues,

Wireless Sensor Networks (WSNs) indicate a group of spatially dispersed and dedicated wireless nodes hosting sensors for monitoring and recording the physical conditions of the environment, and typically collecting data at a central storage location. 

As a more recent development, the Internet of Things (IoT) integrates networked sensors such as WSNs and, more in general, physical objects (i.e., things) in a ubiquitous cyberspace by interconnecting these systems to the Internet at large, making them also available over the web. This is becoming an attractive systems paradigm: indeed, the IoT-enabled approach can remarkably broaden the scope and reach of the data produced and collected by WSNs, as well as the opportunity for machine-to-machine interactions and data consumption at a global scale.

In the following, we use the term IoT-enabled WSN to describe a WSN that also includes an IoT-ready functionality, thus further extending WSNs by including the Internet at large, as well as the web, with its users and their interactions, in the loop. Based on the significant development of a wide variety of powerful sensing/actuating boards, together with advanced networking and communications technologies, researchers and practitioners can obtain an integrated set of controls, data, information and, ultimately, knowledge, borne at the interface between the physical and the virtual world.

However, the large-scale deployment of IoT-enabled WSNs will face a series of challenges and issues (e.g., energy efficiency requirements, architecture, protocol stack design, implementation, security, etc.), which requires smarter transducing and computing methods, as well as advanced networking and communications technologies, to provide more pervasive WSN-powered services for people over the Internet.

This Special Issue aims to attract novel contributions articulating pioneering perspectives, addressing current challenges and open issues within the IoT world at large, and specifically within IoT-enabled WSNs. Authors from both academia and industry are welcome to contribute and demonstrate the latest research results on the design, implementation, deployment, operation and evaluation of smart sensing and computing models, networking methodologies, communications tools and platforms for IoT-enabled WSNs.

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

  • Multi-functional IoT-enabled WSN nodes
  • Smart IoT-ready WSNs and platforms
  • Modelling of IoT-enabled WSNs
  • Energy-efficient IoT-enabled WSNs architectures
  • Green computing and sustainable computing for IoT-enabled WSNs
  • Cloud computing, fog computing and edge computing for IoT and WSNs
  • Routing protocols, data dissemination and offloading algorithms
  • Community detection and network evolution analysis for IoT-enabled WSNs
  • Localization and node mobility models
  • Methods for data collection, convergence and storage
  • Schemes of data mining, processing and analysis
  • Data visualization techniques
  • Quality of Experience and Quality of Service in IoT-enabled WSNs
  • Low-power, distributed data processing in sensor applications
  • Smart cities and smart healthcare
  • Security, privacy and trust for IoT and WSNs
  • Energy harvesting communications and networks
  • Machine learning/deep learning/artificial intelligence approaches
  • Applications and testbeds of IoT-enabled WSNs

Additionally, the 2019 IEEE International Conference on Internet of Things (iThings-2019, http://cse.stfx.ca/~cybermatics/2019/ithings/) will be held in Atlanta, USA, 14–17 July 2019. Selected papers from iThings-2019 with enough additional content will also be included in the Special Issue.

Prof. Dr. Antonio Puliafito
Prof. Dr. Laurence T. Yang
Dr. Giovanni Merlino
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 papers will be 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 2000 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 (2 papers)

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Research

Open AccessArticle
Successive Interference Cancellation Based Throughput Optimization for Multi-Hop Wireless Rechargeable Sensor Networks
Sensors 2020, 20(2), 327; https://doi.org/10.3390/s20020327 - 07 Jan 2020
Abstract
Wireless Sensor Networks are constrained by low channel utilization and limited battery capacity, so they are widely regarded as the mainly performance bottlenecks. In this paper, in order to improve channel utilization and prolong network lifetime, we investigate the cooperation of multi-hop Wireless [...] Read more.
Wireless Sensor Networks are constrained by low channel utilization and limited battery capacity, so they are widely regarded as the mainly performance bottlenecks. In this paper, in order to improve channel utilization and prolong network lifetime, we investigate the cooperation of multi-hop Wireless Rechargeable Sensor Networks (WRSNs) with Successive Interference Cancellation (SIC) technology. In WRSNs, since the flow rate of each node is unknown, the power of the nodes is not constant. However, SIC will not work if the signal power levels at receive node cannot be sorted. To solve this issue, we first construct a minimum energy routing and unify the transmit rate to determine the transmit power. We can also obtain the time scheduling scheme after determining the routing and power. Next, we formulate an optimization problem, with the objective of maximizing the mobile charger’s vacation time over the rechargeable cycle. Finally, we provide a near-optimal solution and prove its feasible performance. Simulation results present that SIC can achieve the better upper boundary on throughput (compared to inference avoidance increasing about 180–450%) and no extra transmit and receive energy consumption in the multi-hop WRSNs. Full article
(This article belongs to the Special Issue IoT-Enabled Sensor Networks: Vision and Challenges)
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Open AccessArticle
Towards Efficient Data Collection in Space-Based Internet of Things
Sensors 2019, 19(24), 5523; https://doi.org/10.3390/s19245523 - 13 Dec 2019
Cited by 1
Abstract
Due to the strong anti-destructive ability, global coverage, and independent infrastructure of the space-based Internet of Things (S-IoT), it is one of the most important ways to achieve a real interconnection of all things. In S-IoT, a single satellite can often achieve thousands [...] Read more.
Due to the strong anti-destructive ability, global coverage, and independent infrastructure of the space-based Internet of Things (S-IoT), it is one of the most important ways to achieve a real interconnection of all things. In S-IoT, a single satellite can often achieve thousands of kilometers of coverage and needs to provide data transmission services for massive ground nodes. However, satellite bandwidth is usually low and the uplink and downlink bandwidth is extremely asymmetric. Therefore, exact data collection is not affordable for S-IoT. In this paper, an approximate data collection algorithm is proposed for S-IoT; that is, the sampling-reconstruction (SR) algorithm. Since the uplink bandwidth is very limited, the SR algorithm samples only the sensory data of some nodes and then reconstructs the unacquired data based on the spatiotemporal correlation between the sensory data. In order to obtain higher data collection precision under a certain data collection ratio, the SR algorithm optimizes the sampling node selection by leveraging the curvature characteristics of the sensory data in time and space dimensions. Moreover, the SR algorithm innovatively applies spatiotemporal compressive sensing (ST-CS) technology to accurately reconstruct unacquired sensory data by making full use of the spatiotemporal correlation between the sensory data. We used a real-weather data set to evaluate the performance of the SR algorithm and compared it with two existing representative approximate data collection algorithms. The experimental results show that the SR algorithm is well-suited for S-IoT and can achieve efficient data collection under the condition that the uplink bandwidth is extremely limited. Full article
(This article belongs to the Special Issue IoT-Enabled Sensor Networks: Vision and Challenges)
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