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Empowering the IoT: Scalable, Sustainable, and Ultra-Low Power Solutions
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Empowering the IoT: Scalable, Sustainable, and Ultra-Low Power Solutions

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

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 2009

Special Issue Editors

Dr. Shimin Gong

E-Mail Website
Guest Editor
School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China
Interests: Internet of Things; backscatter communications; wireless powered transfer; wireless resource optimization, machine learning in wireless systems
Special Issues, Collections and Topics in MDPI journals
Dr. Lanhua Li

E-Mail Website
Guest Editor
School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou 510275, China
Interests: AIoT; backscatter communications; passive sensing systems; UAV communication networks; IRS-assisted wireless communication; and wireless resource optimization
Dr. Yueling Che

E-Mail Website
Guest Editor
College of Computer and Software Engineering, Shenzhen University, Shenzhen 518060, China
Interests: energy-efficient wireless communications and systems; UAV-enabled communication and sensing; AI-enabled wireless communications; wireless powered communications; stochastic modeling and optimization methods
Dr. Kongyang Chen

E-Mail Website
Guest Editor
Institutes of Artificial Intelligence, Guangzhou University, Guangzhou 510006, China
Interests: machine learning security; Internet of Things; edge computing
Special Issues, Collections and Topics in MDPI journals
Dr. Nguyen Cong Luong

E-Mail Website
Guest Editor
Faculty of Computer Science, Phenikaa University, Hanoi 100803, Vietnam
Interests: Internet of Things (IoT); wireless power transfer; intelligent reflecting surface; rate splitting multiple access; digital twin; semantic communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the Internet of Things (IoT) technology continues to evolve, it brings forth a multitude of emerging applications, ranging from smart homes and intelligent unmanned systems to the development of smart cities. These applications hold the promise of transforming our daily lives, but they also bring forth new challenges that must be addressed to ensure the long lifetime of IoT devices and systems. In light of these challenges, it is imperative that we redirect our focus towards the development of IoT solutions capable of supporting widely deployed devices while upholding principles of sustainability, scalability, and energy efficiency.

We are delighted to announce a Special Issue dedicated to exploring scalable, sustainable, and ultra-low-power communication, networking, and sensing technologies in IoT systems. This Special Issue aims to bring together researchers, academics, and industry professionals to address the pressing challenges facing the IoT landscape and to explore innovative solutions that can pave the way for a more sustainable and efficient future.

Potential topics for contributions include, but are not limited to:

  • Strategies for scalable deployment of IoT networks
  • Integration of artificial intelligence to empower IoT systems
  • Efficient resource optimization strategies for IoT networks
  • Wireless power transfer for sustainable IoT implementations
  • Ultra-lower power techniques for integrated sensing and communications
  • Ultra-low power enabled IoT computing and security
  • Ultra-low power enabled IoT systems and platforms
  • Unmanned aerial vehicle assisted IoT networks
  • Reconfigurable intelligent surfaces aided wireless communications
  • Semantic communications for IoT networks

Dr. Shimin Gong
Dr. Lanhua Li
Dr. Yueling Che
Dr. Kongyang Chen
Dr. Nguyen Cong Luong
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 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

  • ultra-low-power IoT
  • edge AI
  • IoT security
  • wireless powered communications
  • integrated sensing, communication and computing
  • UAV
  • RIS
  • semantic communications

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Published Papers (2 papers)

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Research

19 pages, 1868 KiB  
Article
Constrained Flooding Based on Time Series Prediction and Lightweight GBN in BLE Mesh
by Junxiang Li, Mingxia Li and Li Wang
Sensors 2024, 24(14), 4752; https://doi.org/10.3390/s24144752 - 22 Jul 2024
Cited by 1 | Viewed by 597
Abstract
Bluetooth Low Energy Mesh (BLE Mesh) enables Bluetooth flexibility and coverage by introducing Low-Power Nodes (LPNs) and enhanced networking protocol. It is also a commonly used communication method in sensor networks. In BLE Mesh, LPNs are periodically woken to exchange messages in a [...] Read more.
Bluetooth Low Energy Mesh (BLE Mesh) enables Bluetooth flexibility and coverage by introducing Low-Power Nodes (LPNs) and enhanced networking protocol. It is also a commonly used communication method in sensor networks. In BLE Mesh, LPNs are periodically woken to exchange messages in a stop-and-wait way, where the tradeoff between energy and efficiency is a hard problem. Related works have reduced the energy consumption of LPNs mainly in the direction of changing the bearer layer, improving time synchronization and broadcast channel utilization. These algorithms improve communication efficiency; however, they cause energy loss, especially for the LPNs. In this paper, we propose a constrained flooding algorithm based on time series prediction and lightweight GBN (Go-Back-N). On the one hand, the wake-up cycle of the LPNs is determined by the time series prediction of the surrounding load. On the other, LPNs exchange messages through lightweight GBN, which improves the window and ACK mechanisms. Simulation results validate the effectiveness of the Time series Prediction and LlightWeight GBN (TP-LW) algorithm in energy consumption and throughput. Compared with the original algorithm of BLE Mesh, when fewer packets are transmitted, the throughput is increased by 214.71%, and the energy consumption is reduced by 65.14%. Full article
(This article belongs to the Special Issue Empowering the IoT: Scalable, Sustainable, and Ultra-Low Power Solutions)
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26 pages, 3188 KiB  
Article
Deep Reinforcement Learning for Optimizing Restricted Access Window in IEEE 802.11ah MAC Layer
by Xiaojun Jiang, Shimin Gong, Chengyi Deng, Lanhua Li and Bo Gu
Sensors 2024, 24(10), 3031; https://doi.org/10.3390/s24103031 - 10 May 2024
Viewed by 997
Abstract
The IEEE 802.11ah standard is introduced to address the growing scale of internet of things (IoT) applications. To reduce contention and enhance energy efficiency in the system, the restricted access window (RAW) mechanism is introduced in the medium access control (MAC) layer to [...] Read more.
The IEEE 802.11ah standard is introduced to address the growing scale of internet of things (IoT) applications. To reduce contention and enhance energy efficiency in the system, the restricted access window (RAW) mechanism is introduced in the medium access control (MAC) layer to manage the significant number of stations accessing the network. However, to achieve optimized network performance, it is necessary to appropriately determine the RAW parameters, including the number of RAW groups, the number of slots in each RAW, and the duration of each slot. In this paper, we optimize the configuration of RAW parameters in the uplink IEEE 802.11ah-based IoT network. To improve network throughput, we analyze and establish a RAW parameters optimization problem. To effectively cope with the complex and dynamic network conditions, we propose a deep reinforcement learning (DRL) approach to determine the preferable RAW parameters to optimize network throughput. To enhance learning efficiency and stability, we employ the proximal policy optimization (PPO) algorithm. We construct network environments with periodic and random traffic in an NS-3 simulator to validate the performance of the proposed PPO-based RAW parameters optimization algorithm. The simulation results reveal that using the PPO-based DRL algorithm, optimized RAW parameters can be obtained under different network conditions, and network throughput can be improved significantly. Full article
(This article belongs to the Special Issue Empowering the IoT: Scalable, Sustainable, and Ultra-Low Power Solutions)
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