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Energy Efficient Design in Wireless Ad Hoc and Sensor Networks
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Energy Efficient Design in Wireless Ad Hoc and Sensor Networks

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

Deadline for manuscript submissions: closed (20 January 2025) | Viewed by 9860

Special Issue Editors

Dr. Rosario Giuseppe Garroppo

E-Mail Website
Guest Editor
Dipartimento di Ingegneria dell’Informazione, Università di Pisa, Pisa, Italy
Interests: green networks; traffic optimization; traffic control and monitoring in cellular systems; QoE guarantee for MoIP services; routing in WMN; machine learning algorithms for network functions
Special Issues, Collections and Topics in MDPI journals
Dr. Sergio Herrería Alonso

E-Mail Website
Guest Editor
atlanTTic Research Center for Telecommunications Technologies, Universidade de Vigo, 36310 Vigo, Spain
Interests: green networking; quality of service in the internet; performance analysis of computer networks; ICNs & NDN
Special Issues, Collections and Topics in MDPI journals
Dr. Miguel Rodríguez Pérez

E-Mail Website
Guest Editor
Department of Telematics Engineering, University of Vigo, 36310 Vigo, Spain
Interests: green networking; virtualization of network functions and services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wireless ad hoc and sensor networks have become increasingly popular due to their versatility and flexibility in various applications. However, the limited energy resources of these networks have become a critical bottleneck for their deployment and sustainability. Energy-efficient design is essential to ensure the longevity and reliability of these networks, while also reducing their operational and maintenance costs.

This Special Issue focuses on the importance of energy efficiency in wireless ad hoc and sensor networks, highlighting the key challenges and potential solutions for addressing energy constraints. The Special Issue will also explore the role of emerging technologies, such as the Internet of Things (IoT) and Beyond 5G, in the development of energy-efficient wireless ad hoc and sensor networks.

The topics covered in this Special Issue include, but are not limited to, energy-efficient routing protocols, modulation and coding schemes, MAC protocols, and network architectures. This Special Issue also welcomes research on the integration of machine learning and artificial intelligence in energy-efficient design. Overall, this Special Issue aims to provide a comprehensive overview of the state-of-the-art research in energy-efficient design in wireless ad hoc and sensor networks, and to stimulate further research and development in this important area.

Topics of interest include, but are not limited to:

  • Energy-efficient routing protocols
  • Energy-efficient MAC protocols
  • Data aggregation and compression techniques for sensor networks
  • Localization and tracking algorithms for green ad hoc and sensor networks
  • Data dissemination and gathering techniques for green ad hoc and sensor networks
  • Sensor network deployment strategies and optimization techniques
  • Scheduling and resource allocation for green communications
  • Software and hardware design
  • Green home networks
  • Novel network architectures for green ad hoc and sensor networks
  • Energy-efficient transport layer protocols
  • Machine learning approaches for energy management
  • Green satellite communications
  • Energy saving opportunities in information-centric networks

Dr. Rosario Giuseppe Garroppo
Dr. Sergio Herrería Alonso
Dr. Miguel Rodríguez Pérez
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.

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Published Papers (7 papers)

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Research

17 pages, 1538 KiB  
Article
AI-Driven Adaptive Communications for Energy-Efficient Underwater Acoustic Sensor Networks
by A. Ur Rehman, Laura Galluccio and Giacomo Morabito
Sensors 2025, 25(12), 3729; https://doi.org/10.3390/s25123729 - 14 Jun 2025
Viewed by 884
Abstract
Underwater acoustic sensor networks, crucial for marine monitoring, face significant challenges, including limited bandwidth, high delay, and severe energy constraints. Addressing these limitations requires an energy-efficient design to ensure network survivability, reliability, and reduced operational costs. This paper proposes an artificial intelligence-driven framework [...] Read more.
Underwater acoustic sensor networks, crucial for marine monitoring, face significant challenges, including limited bandwidth, high delay, and severe energy constraints. Addressing these limitations requires an energy-efficient design to ensure network survivability, reliability, and reduced operational costs. This paper proposes an artificial intelligence-driven framework aimed at enhancing energy efficiency and sustainability in applications of marine wildlife monitoring in underwater sensor networks, according to the vision of implementing an underwater acoustic sensor network. The framework integrates intelligent computing directly into underwater sensor nodes, employing lightweight AI models to locally classify marine species. Transmitting only classification results, instead of raw data, significantly reduces data volume, thus conserving energy. Additionally, a software-defined radio methodology dynamically adapts transmission parameters such as modulation schemes, packet length, and transmission power to further minimize energy consumption and environmental disruption. GNU Radio simulations evaluate the framework effectiveness using metrics like energy consumption, bit error rate, throughput, and delay. Adaptive transmission strategies implicitly ensure reduced energy usage as compared to non-adaptive transmission solutions employing fixed communication parameters. The results illustrate the framework ability to effectively balance energy efficiency, performance, and ecological impact. This research contributes directly to ongoing development in sustainable and energy-efficient underwater wireless sensor network design and deployment. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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27 pages, 1065 KiB  
Article
Priority-Aware Spectrum Management for QoS Optimization in Vehicular IoT
by Adeel Iqbal, Tahir Khurshaid, Yazdan Ahmad Qadri, Ali Nauman and Sung Won Kim
Sensors 2025, 25(11), 3342; https://doi.org/10.3390/s25113342 - 26 May 2025
Cited by 1 | Viewed by 522
Abstract
Vehicular Internet of Things (V-IoT) networks, sustained by a high-density deployment of roadside units and sensor-equipped vehicles, are currently at the edge of next-generation intelligent transportation system evolution. However, offering stable, low-latency, and energy-efficient communication in such heterogeneous and delay-prone environments is challenging [...] Read more.
Vehicular Internet of Things (V-IoT) networks, sustained by a high-density deployment of roadside units and sensor-equipped vehicles, are currently at the edge of next-generation intelligent transportation system evolution. However, offering stable, low-latency, and energy-efficient communication in such heterogeneous and delay-prone environments is challenging due to limited spectral resources and diverse quality of service (QoS) requirements. This paper presents a Priority-Aware Spectrum Management (PASM) scheme for IoT-based vehicular networks. This dynamic spectrum access scheme integrates interweave, underlay, and coexistence modes to optimize spectrum utilization, energy efficiency, and throughput while minimizing blocking and interruption probabilities. The algorithm manages resources efficiently and gives proper attention to each device based on its priority, so all IoT devices, from high to low priority, receive continuous and reliable service. A Continuous-Time Markov Chain (CTMC) model is derived to analyze the proposed algorithm for various network loads. Simulation results indicate improved spectral efficiency, throughput, delay, and overall QoS compliance over conventional access methods. These findings establish that the proposed algorithm is a scalable solution for dynamic V-IoT environments. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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33 pages, 2058 KiB  
Article
An Analytical Framework for Optimizing the Renewable Energy Dimensioning of Green IoT Systems in Pipeline Monitoring
by Godlove Suila Kuaban, Valery Nkemeni and Piotr Czekalski
Sensors 2025, 25(10), 3137; https://doi.org/10.3390/s25103137 - 15 May 2025
Cited by 1 | Viewed by 616
Abstract
The increasing demand for sustainable and autonomous monitoring solutions in critical infrastructure has driven interest in Green Internet of Things (G-IoT) systems. This paper presents an analytical and experimental framework for designing energy-efficient, self-sustaining pipeline monitoring systems that leverage renewable energy harvesting and [...] Read more.
The increasing demand for sustainable and autonomous monitoring solutions in critical infrastructure has driven interest in Green Internet of Things (G-IoT) systems. This paper presents an analytical and experimental framework for designing energy-efficient, self-sustaining pipeline monitoring systems that leverage renewable energy harvesting and low-power operation techniques. We propose a hybrid approach combining solar energy harvesting with energy-saving strategies such as adaptive sensing, duty cycling, and distributed computing to extend the lifetime of IoT nodes without human intervention. Using real-world irradiance data and energy profiling from a prototype testbed, we analyze the impact of solar panel sizing, energy storage capacity, energy-saving strategies, and energy leakage on the energy balance of IoT nodes. The simulation results show that, with optimal dimensioning, harvested solar energy can sustain pipeline monitoring operations over multi-year periods, even under variable environmental conditions. We investigated the influence of design parameters such as duty cycling, solar panel area, the capacity of the energy storage system, and the energy leakage coefficient on energy performance metrics such as the autonomy or lifetime of the node (time required to drain all the stored energy), which is an important design object. This framework provides practical design insights for the scalable deployment of G-IoT systems in energy-constrained outdoor environments. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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18 pages, 918 KiB  
Article
Self-Organizing and Routing Approach for Condition Monitoring of Railway Tunnels Based on Linear Wireless Sensor Network
by Haibo Yang, Huidong Guo, Junying Jia, Zhengfeng Jia and Aiyang Ren
Sensors 2024, 24(20), 6502; https://doi.org/10.3390/s24206502 - 10 Oct 2024
Cited by 1 | Viewed by 1182
Abstract
Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a [...] Read more.
Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a linear topology known as a thick Linear Wireless Sensor Network (LWSN). In practice, sensors are deployed randomly within the area, and to balance the energy consumption among nodes and extend the network’s lifespan, this paper proposes a self-organizing network and routing method based on thick LWSNs. This method can discover the topology, form the network from randomly deployed sensor nodes, establish adjacency relationships, and automatically form clusters using a timing mechanism. In the routing, considering the cluster heads’ load, residual energy, and the distance to the sink node, the optimal next-hop cluster head is selected to minimize energy disparity among nodes. Simulation experiments demonstrate that this method has significant advantages in balancing network energy and extending network lifespan for LWSNs. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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17 pages, 29455 KiB  
Article
FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications
by Ruan C. M. Teixeira, Celso B. Carvalho, Carlos T. Calafate, Edjair Mota, Rubens A. Fernandes, Andre L. Printes and Lennon B. F. Nascimento
Sensors 2024, 24(19), 6218; https://doi.org/10.3390/s24196218 - 26 Sep 2024
Cited by 1 | Viewed by 2058
Abstract
Monitoring vast and remote areas like forests using Wireless Sensor Networks (WSNs) presents significant challenges, such as limited energy resources and signal attenuation over long distances due to natural obstacles. Traditional solutions often require extensive infrastructure, which is impractical in such environments. To [...] Read more.
Monitoring vast and remote areas like forests using Wireless Sensor Networks (WSNs) presents significant challenges, such as limited energy resources and signal attenuation over long distances due to natural obstacles. Traditional solutions often require extensive infrastructure, which is impractical in such environments. To address these limitations, we introduce the “FloatingBlue” architecture. This architecture, known for its superior energy efficiency, combines Bluetooth Low Energy (BLE) technology with Delay Tolerant Networks (DTN) and data mules. It leverages BLE’s low power consumption for energy-efficient sensor broadcasts while utilizing DTN-enabled data mules to collect data from dispersed sensors without constant network connectivity. Deployed in a remote agricultural area in the Amazon region, “FloatingBlue” demonstrated significant improvements in energy efficiency and communication range, with a high Packet Delivery Ratio (PDR). The developed BLE beacon sensor achieved state-of-the-art energy consumption levels, using only 2.25 µJ in sleep mode and 11.8 µJ in transmission mode. Our results highlight “FloatingBlue” as a robust, low-power solution for remote monitoring in challenging environments, offering an energy-efficient and scalable alternative to traditional WSN approaches. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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27 pages, 7773 KiB  
Article
Charging Scheduling Method for Wireless Rechargeable Sensor Networks Based on Energy Consumption Rate Prediction for Nodes
by Songjiang Huang, Chao Sha, Xinyi Zhu, Jingwen Wang and Ruchuan Wang
Sensors 2024, 24(18), 5931; https://doi.org/10.3390/s24185931 - 12 Sep 2024
Cited by 4 | Viewed by 1937
Abstract
With the development of the IoT, Wireless Rechargeable Sensor Networks (WRSNs) derive more and more application scenarios with diverse performance requirements. In scenarios where the energy consumption rate of sensor nodes changes dynamically, most existing charging scheduling methods are not applicable. The incorrect [...] Read more.
With the development of the IoT, Wireless Rechargeable Sensor Networks (WRSNs) derive more and more application scenarios with diverse performance requirements. In scenarios where the energy consumption rate of sensor nodes changes dynamically, most existing charging scheduling methods are not applicable. The incorrect estimation of node energy requirement may lead to the death of critical nodes, resulting in missing events. To address this issue, we consider both the spatial imbalance and temporal dynamics of the energy consumption of the nodes, and minimize the Event Missing Rate (EMR) as the goal. Firstly, an Energy Consumption Balanced Tree (ECBT) construction method is proposed to prolong the lifetime of each node. Then, we transform the goal into Maximizing the value of the Evaluation function of each node’s Energy Consumption Rate prediction (MEECR). Afterwards, the setting of the evaluation function is explored and the MEECR is further transformed into a variant of the knapsack problem, namely “the alternating backpack problem”, and solved by dynamic programming. After predicting the energy consumption rate of the nodes, a charging scheduling scheme that meets the Dual Constraints of Nodes’ energy requirements and MC’s capability (DCNM) is developed. Simulations demonstrate the advantages of the proposed method. Compared to the baselines, the EMR was reduced by an average of 35.2% and 26.9%. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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14 pages, 675 KiB  
Article
Unmanned Aerial Vehicle-Based Compressed Data Acquisition for Environmental Monitoring in WSNs
by Cuicui Lv, Linchuang Yang, Xinxin Zhang, Xiangming Li, Peijin Wang and Zhenbin Du
Sensors 2023, 23(20), 8546; https://doi.org/10.3390/s23208546 - 18 Oct 2023
Cited by 2 | Viewed by 1590
Abstract
With the increasing concerns for the environment, the amount of the data monitored by wireless sensor networks (WSNs) is becoming larger and the energy required for data transmission is greater. However, sensor nodes have limited storage capacity and battery power. The WSNs are [...] Read more.
With the increasing concerns for the environment, the amount of the data monitored by wireless sensor networks (WSNs) is becoming larger and the energy required for data transmission is greater. However, sensor nodes have limited storage capacity and battery power. The WSNs are faced with the challenge of handling larger data volumes while minimizing energy consumption for transmission. To address this issue, this paper employs data compression technology to eliminate redundant information in the environmental data, thereby reducing energy consumption of sensor nodes. Additionally, an unmanned aerial vehicle (UAV)-assisted compressed data acquisition algorithm is put forward. In this algorithm, compressive sensing (CS) is introduced to decrease the amount of data in the network and the UAV serves as a mobile aerial base station for efficient data gathering. Based on CS theory, the UAV selectively collects measurements from a subset of sensor nodes along a route planned using the optimized greedy algorithm with variation and insertion strategies. Once the UAV returns, the sink node reconstructs sensory data from these measurements using the reconstruction algorithms. Extensive experiments are conducted to verify the performance of this algorithm. Experimental results show that the proposed algorithm has lower energy consumption compared to other approaches. Furthermore, we employ different data reconstruction algorithms to recover data and discover that the data can be better reconstructed in a shorter time. Full article
(This article belongs to the Special Issue Energy Efficient Design in Wireless Ad Hoc and Sensor Networks)
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