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Lifetime Extension Framework for Wireless Sensor Networks

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

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 13050

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Special Issue Editors

Prof. Dr. Konstantinos Oikonomou

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Department of Informatics, Faculty of Information Science and Informatics, Ionian University, 49100 Corfu, Greece
Interests: medium access control in ad hoc networks; performance issues in wireless networks; information dissemination; service discovery; facility location; energy consumption and recharging in wireless sensor networks; network cost reduction in cloud computing environments; routing in wireless sensor networks; MAC for vehicular networks; synchronization issues in distributed systems; cloud gaming; smart agriculture
Special Issues, Collections and Topics in MDPI journals

Dr. Constantinos Angelis

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Guest Editor

Department of Informatics and Telecommunications, Campus of Arta, University of Ioannina, 47100 Arta, Greece
Interests: wireless sensor networks; wireless telecommunication systems; designs and implementations
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Dr. Georgios Tsoumanis

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Guest Editor

Department of Informatics & Telecommunications, Faculty of Informatics & Telecommunications, University of Ioannina, 47100 Arta, Greece
Interests: facility location; computer networking; network simulation; programming; sensor networks; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the past decades, wireless sensor networks (WSNs) have experienced exceptional growth, their success reflecting their continuously increasing areas of application (e.g., area monitoring, environmental sensing, threat detection, etc.). Besides, the integration of WSNs in the IoT allows the latter to penetrate deeply into our daily lives and provide various convenient services enabling users to access, use, and process information collected from sensors through smart devices.

On the one hand, WSN devices' small size and low cost allow for development in large-scale environments. On the other hand, in the absence of infrastructure (due to their wireless nature), their operation depends on their limited batteries' energy supply. As a result of the limitations deriving from the low-capacity batteries, the lifetime of a WSN is inextricably linked to them. Thus, the framework underlying the devices' energy usage plays a vital role in the network's overall energy consumption and lifetime. For example, minimizing the number of packet transmissions among the WSN nodes or choosing a better location for the sink node can result in a lifetime extension.

Apart from optimizing the energy consumption, another way to increase a WSN's lifetime is to find an optimal way to recharge its nodes' batteries. In these so-called Rechargeable Wireless Sensor Networks (RWSNs), a vehicle (e.g., an unmanned autonomous vehicle, a drone, etc.) able to recharge the nodes' batteries is implemented and moves among the nodes replenishing their batteries. To take advantage of this procedure and maximize the lifetime of the RWSN and the recharging vehicle itself, a framework (or policy) on which the recharging vehicle bases its operation must be considered. This framework has to take into account issues such as the minimization of the distance travelled by the recharging vehicle to recharge the nodes, the optimization of the number of visited (for a replenishment) nodes, the minimization of the energy consumption of the vehicle, among others.

This Special Issue invites original research papers on new frameworks, algorithms, protocols, architectures, technologies, and solutions for extending the lifetime of a WSN (or RWSN). Relevant topics include, but are not limited to:

- Lifetime extension

- Energy consumption optimization

- Energy-efficient routing

- Load balancing

- Optimal location of WSN nodes

- Optimal location of sink node(s)

- Machine learning-based WSN techniques

- AI-enabled routing

- Optimal data collection

- Data reduction/compression

- Wireless energy transfer techniques

- Joint information and energy transfer

- Energy harvesting

- Recharging vehicles

- Simulation tools

- Physical layer challenges, issues, and solutions

- Mobile edge/fog computing

Dr. Konstantinos Oikonomou
Dr. Constantinos Angelis
Dr. Georgios Tsoumanis
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.

Published Papers (5 papers)

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Research

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24 pages, 1173 KiB

Open AccessArticle

RealPrice: Blockchain-Powered Real-Time Pricing for Software-Defined Enabled Edge Network

by Yustus Eko Oktian, Thi-Thu-Huong Le, Uk Jo and Howon Kim

Sensors 2022, 22(24), 9639; https://doi.org/10.3390/s22249639 - 08 Dec 2022

Cited by 1 | Viewed by 1119

Abstract

With the limited Internet bandwidth in a given area, unlimited data plans can create congestion because there is no retribution for transmitting many packets. The real-time pricing mechanism can inform users of their Internet consumption to limit congestion during peak hours. However, implementing real-time pricing is opex-heavy from the network provider side and requires high-integrity operations to gain consumer trust. This paper aims to leverage the software-defined network to solve the opex issues and blockchain technology to solve trust issues. First, the network congestion level in a given area is analyzed. Then, the price is adjusted accordingly. Devices that send a lot of traffic during congestion will be charged more expensive bills than if transmitting traffic during an off-peak period. To prevent over-charging, the consumers can pre-configure a customized Internet profile stating how many data bytes they are willing to send during congestion. The software-defined controller also authenticates consumers and checks whether they have enough token deposits in the blockchain as Internet usage fees. We implement our work using Ethereum and POX controllers. The experiment results show that the proposed real-time pricing can be performed seamlessly, and the network provider can reap up to 72.91% more profits than existing approaches, such as usage-based pricing or time-dependent pricing. The fairness and trustability of real-time pricing is also guaranteed through the proof-of-usage mechanism and the transparency of the blockchain. Full article

(This article belongs to the Special Issue Lifetime Extension Framework for Wireless Sensor Networks)

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18 pages, 988 KiB

Open AccessArticle

An Effective Self-Configurable Ransomware Prevention Technique for IoMT

by Usman Tariq, Imdad Ullah, Mohammed Yousuf Uddin and Se Jin Kwon

Sensors 2022, 22(21), 8516; https://doi.org/10.3390/s22218516 - 04 Nov 2022

Cited by 4 | Viewed by 2387

Abstract

Remote healthcare systems and applications are being enabled via the Internet of Medical Things (IoMT), which is an automated system that facilitates the critical and emergency healthcare services in urban areas, in addition to, bridges the isolated rural communities for various healthcare services. Researchers and developers are, to date, considering the majority of the technological aspects and critical issues around the IoMT, e.g., security vulnerabilities and other cybercrimes. One of such major challenges IoMT has to face is widespread ransomware attacks; a malicious malware that encrypts the patients’ critical data, restricts access to IoMT devices or entirely disable IoMT devices, or uses several combinations to compromise the overall system functionality, mainly for ransom. These ransomware attacks would have several devastating consequences, such as loss of life-threatening data and system functionality, ceasing emergency and life-saving services, wastage of several vital resources etc. This paper presents a ransomware analysis and identification architecture with the objective to detect and validate the ransomware attacks and to evaluate its accuracy using a comprehensive verification process. We first develop a comprehensive experimental environment, to simulate a real-time IoMT network, for experimenting various types of ransomware attacks. Following, we construct a comprehensive set of ransomware attacks and analyze their effects over an IoMT network devices. Furthermore, we develop an effective detection filter for detecting various ransomware attacks (e.g., static and dynamic attacks) and evaluate the degree of damages caused to the IoMT network devices. In addition, we develop a defense system to block the ransomware attacks and notify the backend control system. To evaluate the effectiveness of the proposed framework, we experimented our architecture with 194 various samples of malware and 46 variants, with a duration of sixty minutes for each sample, and thoroughly examined the network traffic data for malicious behaviors. The evaluation results show more than 95% of accuracy of detecting various ransomware attacks. Full article

(This article belongs to the Special Issue Lifetime Extension Framework for Wireless Sensor Networks)

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18 pages, 595 KiB

Open AccessArticle

Coverage Path Planning and Point-of-Interest Detection Using Autonomous Drone Swarms

by Konstantinos Bezas, Georgios Tsoumanis, Constantinos T. Angelis and Konstantinos Oikonomou

Sensors 2022, 22(19), 7551; https://doi.org/10.3390/s22197551 - 05 Oct 2022

Cited by 9 | Viewed by 2100

Abstract

Unmanned Aerial Vehicles (UAVs) or drones presently are enhanced with miniature sensors that can provide information relative to their environment. As such, they can detect changes in temperature, orientation, altitude, geographical location, electromagnetic fluctuations, lighting conditions, and more. Combining this information properly can help produce advanced environmental awareness; thus, the drone can navigate its environment autonomously. Wireless communications can also aid in the creation of drone swarms that, combined with the proper algorithm, can be coordinated towards area coverage for various missions, such as search and rescue. Coverage Path Planning (CPP) is the field that studies how drones, independently or in swarms, can cover an area of interest efficiently. In the current work, a CPP algorithm is proposed for a swarm of drones to detect points of interest and collect information from them. The algorithm’s effectiveness is evaluated under simulation results. A set of characteristics is defined to describe the coverage radius of each drone, the speed of the swarm, and the coverage path followed by it. The results show that, for larger swarm sizes, the missions require less time while more points of interest can be detected within the area. Two coverage paths are examined here—parallel lines and spiral coverage. The results depict that the parallel lines coverage is more time-efficient since the spiral increases the required time by an average of 5% in all cases for the same number of detected points of interest. Full article

(This article belongs to the Special Issue Lifetime Extension Framework for Wireless Sensor Networks)

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25 pages, 3397 KiB

Open AccessArticle

Energy-Aware QoS MAC Protocol Based on Prioritized-Data and Multi-Hop Routing for Wireless Sensor Networks

by Aan Nazmus Sakib, Micheal Drieberg, Sohail Sarang, Azrina Abd Aziz, Nguyen Thi Thu Hang and Goran M. Stojanović

Sensors 2022, 22(7), 2598; https://doi.org/10.3390/s22072598 - 29 Mar 2022

Cited by 11 | Viewed by 2800

Abstract

Wireless sensor networks (WSNs) have received considerable interest in recent years. These sensor nodes can gather information from the surrounding environment and transmit it to a designated location. Each sensor node in WSN typically has a battery with a limited capacity. Due to their large number and because of various environmental challenges, it is sometimes hard to replace this finite battery. As a result, energy-efficient communication is seen as a critical aspect in extending the lifespan of a sensor node. On the other hand, some applications that require large coverage and generate various sorts of data packets require multi-hop routing and quality of service (QoS) features. Therefore, in order to avoid network failure, these applications need an energy-efficient QoS MAC protocol that can support multiple levels of data packet priority and multi-hop routing features while focusing on energy conservation. An energy-aware QoS MAC protocol based on Prioritized Data and Multi-hop routing (EQPD-MAC) is proposed in this article. The EQPD-MAC protocol offers a simple yet effective cross-layer communication method. It provides timely delivery of multi-priority packets, uses an adaptive active time to limit idle listening, and integrates a robust routing protocol. Finally, the EQPD-MAC protocol’s performance was evaluated and compared to three other well-known QoS MAC protocols. The simulation findings show that the proposed protocol significantly decreases sensor node energy consumption by up to 30.3%, per-bit energy consumption by up to 29.6%, sink node energy consumption by up to 27.4% and increases throughput by up to 23.3%. Full article

(This article belongs to the Special Issue Lifetime Extension Framework for Wireless Sensor Networks)

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Review

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35 pages, 8647 KiB

Open AccessReview

Perovskite Piezoelectric-Based Flexible Energy Harvesters for Self-Powered Implantable and Wearable IoT Devices

by Srinivas Pattipaka, Young Min Bae, Chang Kyu Jeong, Kwi-Il Park and Geon-Tae Hwang

Sensors 2022, 22(23), 9506; https://doi.org/10.3390/s22239506 - 05 Dec 2022

Cited by 7 | Viewed by 3344

Abstract

In the ongoing fourth industrial revolution, the internet of things (IoT) will play a crucial role in collecting and analyzing information related to human healthcare, public safety, environmental monitoring and home/industrial automation. Even though conventional batteries are widely used to operate IoT devices as a power source, these batteries have a drawback of limited capacity, which impedes broad commercialization of the IoT. In this regard, piezoelectric energy harvesting technology has attracted a great deal of attention because piezoelectric materials can convert electricity from mechanical and vibrational movements in the ambient environment. In particular, piezoelectric-based flexible energy harvesters can precisely harvest tiny mechanical movements of muscles and internal organs from the human body to produce electricity. These inherent properties of flexible piezoelectric harvesters make it possible to eliminate conventional batteries for lifetime extension of implantable and wearable IoTs. This paper describes the progress of piezoelectric perovskite material-based flexible energy harvesters for self-powered IoT devices for biomedical/wearable electronics over the last decade. Full article

(This article belongs to the Special Issue Lifetime Extension Framework for Wireless Sensor Networks)

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