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Special Issue "Challenges, Trade-offs, and Experiences for Edge Computing in Wireless Sensor Networks"

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

Deadline for manuscript submissions: 15 September 2020.

Special Issue Editors

Prof. Dr. Allessandro Mecocci
Website
Guest Editor
Advanced Digital Image Processing, Department of Information Engineering and Mathematics, University of Siena, via Roma 56, 53100 Siena, Italy
Interests: computer vision, pattern recognition, autonomous learning systems, homeland safety, videosurveillance, cultural heritage preservation
Prof. Dr. Sandro Bartolini
Website
Guest Editor
Department of Information Engineering and Mathematics, University of Siena, via Roma 56, 53100 Siena, Italy
Interests: high-efficiency computer architecture, parallel processing, produtivity-oriented parallel programming, information security, service-oriented architectures
Dr. Alessandro Pozzebon
Website SciProfiles
Guest Editor
Department of Information Engineering and Mathematics, University of Siena, via Roma 56, 53100 Siena, Italy
Interests: Internet of Things; wireless sensor networks; LPWA networks; ZigBee; mobile technologies
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The vast diffusion of wirelessly connected intelligent devices is rapidly changing the approach towards the design of monitoring infrastructures in several application fields. The availability of low-cost data-processing devices is moving part of the computation load towards the edge of the network. This leads to the definition of a wide range of new application scenarios. In particular, intelligent wireless sensor networks open up the way for the realization of monitoring infrastructures based on sensors that require mixed use of computationally light sensors (e.g., pressure sensors, thermal sensors, sound sensors), up to computationally heavy ones (e.g., cameras and 3D range sensors), to implement distributed, scalable, flexible, and resilient systems.

Data processing at the edge of the network, nevertheless, poses several technological challenges, in terms of security and reliability, as well as energy efficiency and management, network connectivity, timing constraints, and orchestration. And, crucially, in the vast majority of situations, multiple facets need to be addressed together and induce the design and management of nontrivial trade-offs.

This Special Issue invites original contributions on topics including, but not limited to, the following arguments:

 

  • Wireless data transmission techniques for intelligent sensor networks;
  • Data summarization and data interpolation that also accounts for spatial and temporal information;
  • Integration between fixed and mobile sensors, including drone-based ones;
  • Imaging and multimedia data management in wireless sensor networks;
  • Energy policies and trade-offs;
  • Security and reliability in the architectural design of wireless sensor networks;
  • Energy harvesting techniques and implications for intelligent sensor nodes and networks;
  • Hierarchical design of the architecture and functions;
  • Dynamic role reconfiguration in nodes and networks;
  • Programmability and performance/energy efficiency;
  • Timing constrains in surveillance and monitoring; and
  • Applications, best practices, and real-world examples based on intelligent sensor nodes/networks.

Prof. Dr. Allessandro Mecocci
Prof. Dr. Sandro Bartolini
Dr. Alessandro Pozzebon
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.

Keywords

  • wireless sensor networks
  • edge computing
  • fog computing
  • security
  • reliability
  • energy harvesting
  • power management

Published Papers (1 paper)

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Research

Open AccessArticle
An Energy-Efficient and Adaptive Channel Coding Approach for Narrowband Internet of Things (NB-IoT) Systems
Sensors 2020, 20(12), 3465; https://doi.org/10.3390/s20123465 - 19 Jun 2020
Abstract
Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the [...] Read more.
Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the network’s reliability and therefore, enabling long-distance transmissions. Although most of these efforts are made at the expense of reducing the energy consumption of the NB-IoT network, they do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy-Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only selects an appropriate channel coding scheme based on the estimated channel conditions (dynamically classified as bad, medium or good from initial based on a periodically assessed BLER performance outcome) but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission (based on the ratio of previous successful transmissions over the total number of transmissions). This results in creating a single mixed gradient based on which a higher or lower Modulating Coding Scheme (MCS) is selected on each transmission. It is aimed at enhancing the overall energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions (good, medium, or bad) considerations to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes in terms of the achieved energy efficiency as well as network reliability, latency, and scalability. Full article
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