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Energy Harvesting Communication and Computing Systems
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Energy Harvesting Communication and Computing Systems

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 9759

Special Issue Editor

Prof. Dr. Maryline Chetto

E-Mail Website
Guest Editor
Département Qualité, Logistique Industrielle et Organisation, Nantes Université, Ecole Centrale Nantes, CNRS, LS2N, UMR 6004, F-44000 Nantes, France
Interests: real-time scheduling; energy management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote and unattended sensors require that computation and communication be performed without human intervention to replace batteries, and without a connection to the mains power source. Thus, there is a strong motivation to overcome the energy limitations of conventional systems by relying on energy harvesting. This can occur by continuously extracting energy from a renewable energy source present in the surrounding environment, and by storing it for future use. Multiple sources of energy can be exploited, such as solar power, wind, mechanical vibrations, temperature variations, etc.

The field of energy harvesting has gained considerable interest over the last decade and promises a wide range of applications in environmental monitoring, as well as applications in human health, defense, agriculture, and industry. Nevertheless, a lot of technical challenges lie ahead so as to make energy harvesting wireless devices work effectively and operate perpetually under an energy-neutral mode. Such systems are exposed to specific and complex issues, mainly due to the uncertainty of energy availability, limited energy storage capacity, and instability of the energy sources.

Research around energy harvesting (EH) sensors comprises various models and techniques, software as well as hardware ranging from, but not limited to, techniques of energy harvesting, power management, harvesting-aware scheduling, harvesting-aware communication protocols, prediction models, etc.

We invite manuscripts for this forthcoming Special Issue in all aspects pertinent to energy autonomous computing/communication systems. Both survey and original research articles are welcome. We look forward to and welcome your participation in this Special Issue.

Prof. Dr. Maryline Chetto
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

  • Information and communications technology for EH sensors
  • Dynamic power management for EH sensors
  • EH aware communication protocols
  • Energy-neutral or power-neutral systems
  • Scheduling with real-time and EH constraints
  • Prototypes and applications with EH technology
  • EH for the Internet of Things

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Published Papers (3 papers)

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Research

17 pages, 881 KiB  
Article
Achievable Rate Maximization for Multi-Relay AF Cooperative SWIPT Systems with a Nonlinear EH Model
by Yizhi Feng and Yan Cao
Sensors 2022, 22(8), 3041; https://doi.org/10.3390/s22083041 - 15 Apr 2022
Cited by 4 | Viewed by 1888
Abstract
In this paper, the maximization of the achievable information rate is proposed for the multi-relay amplify-and-forward cooperative simultaneous wireless information and power transfer communication systems, where the nonlinear characteristic of the energy harvesting (EH) circuits is taken into account for the receivers of [...] Read more.
In this paper, the maximization of the achievable information rate is proposed for the multi-relay amplify-and-forward cooperative simultaneous wireless information and power transfer communication systems, where the nonlinear characteristic of the energy harvesting (EH) circuits is taken into account for the receivers of the relay nodes. The time switching (TS) and power splitting (PS) schemes are considered for the EH receivers and the achievable rate maximization problems are formulated as convex and non-convex optimization problems, respectively. The optimal TS and PS ratios for the relay nodes along with the maximum achievable rates for the system are obtained, respectively, by solving the optimal problems with efficient algorithms. The asymptotic maximum achievable rates at low and high input signal-to-noise ratios (SNRs) for both the PS and TS schemes are also analyzed. It is demonstrated that the PS scheme is more susceptible to the variation of the relays’ location and the channel parameters than TS scheme, whereas the TS scheme is more susceptible to the mismatch of the resource allocation than PS scheme. Specifically, compared to the linear EH model, the nonlinear EH model achieves significant performance gain for the TS scheme, whereas inconspicuous performance improvement is achieved for the PS scheme. Full article
(This article belongs to the Special Issue Energy Harvesting Communication and Computing Systems)
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19 pages, 658 KiB  
Article
Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting
by Philip-Dylan Gleonec, Jeremy Ardouin, Matthieu Gautier and Olivier Berder
Sensors 2021, 21(8), 2874; https://doi.org/10.3390/s21082874 - 19 Apr 2021
Cited by 8 | Viewed by 3522
Abstract
Many connected devices are expected to be deployed during the next few years. Energy harvesting appears to be a good solution to power these devices but is not a reliable power source due to the time-varying nature of most energy sources. It is [...] Read more.
Many connected devices are expected to be deployed during the next few years. Energy harvesting appears to be a good solution to power these devices but is not a reliable power source due to the time-varying nature of most energy sources. It is possible to harvest energy from multiple energy sources to tackle this problem, thus increasing the amount and the consistency of harvested energy. Additionally, a power management system can be implemented to compute how much energy can be consumed and to allocate this energy to multiple tasks, thus adapting the device quality of service to its energy capabilities. The goal is to maximize the amount of measured and transmitted data while avoiding power failures as much as possible. For this purpose, an industrial sensor node platform was extended with a multi-source energy-harvesting circuit and programmed with a novel energy-allocation system for multi-task devices. In this paper, a multi-source energy-harvesting LoRaWAN node is proposed and optimal energy allocation is proposed when the node runs different sensing tasks. The presented hardware platform was built with off-the-shelf components, and the proposed power management system was implemented on this platform. An experimental validation on a real LoRaWAN network shows that a gain of 51% transmitted messages and 62% executed sensing tasks can be achieved with the multi-source energy-harvesting and power-management system, compared to a single-source system. Full article
(This article belongs to the Special Issue Energy Harvesting Communication and Computing Systems)
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18 pages, 2086 KiB  
Article
Online Learning Approach for Predictive Real-Time Energy Trading in Cloud-RANs
by Wan Nur Suryani Firuz Wan Ariffin, Xinruo Zhang, Mohammad Reza Nakhai, Hasliza A. Rahim and R. Badlishah Ahmad
Sensors 2021, 21(7), 2308; https://doi.org/10.3390/s21072308 - 25 Mar 2021
Cited by 4 | Viewed by 3164
Abstract
Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in [...] Read more.
Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in cloud radio access networks (Cloud-RANs). The proposed algorithm employs a combinatorial multi-armed bandit model and minimizes the long-term energy cost at remote radio heads. The algorithm preschedules a set of cost-efficient energy packages to be purchased from an ancillary energy market for the future time slots by learning both from cooperative energy trading at previous time slots and by exploring new energy scheduling strategies at the current time slot. The simulation results confirm a significant performance gain of the proposed scheme in controlling the available power budgets and minimizing the overall energy cost compared with recently proposed approaches for real-time energy resources and energy trading in Cloud-RANs. Full article
(This article belongs to the Special Issue Energy Harvesting Communication and Computing Systems)
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