Top Research Papers on Wireless Sensor Networks

An Intelligent Clustering approach for ITS (ICITS) is proposed which selects CHs based on a hybrid optimization method called GABAT that integrates the strengths of Genetic Algorithm (GA) and BAT Al algorithm (BA) that is targeted primarily to road transport in military areas.

Introduction to Wireless Sensor Networks Applications and Motivation Network Performance Objectives Contributions of this Book Organization of this Book The Development of Wireless Sensor Networks Early Wireless Networks Wireless Data Networks Wireless Sensor and Related Networks Conclusion The Physical Layer Some Physical Layer Examples A Practical Physical Layer for Wireless Sensor Networks Simulations and Results Conclusion The Data Link Layer Medium Access Control Techniques The Mediation Device System Analysis and Simulation Conclusion The Network Layer Some Network Design Examples A Wire...

WIRELESS SENSOR NETWORKS: ARCHITECTURES AND PROTOCOLS

As Wireless Sensor Networks (WSNs) and Internet of Things (IoTs) applications evolve, the need for robust protocols, capable to guarantee extended lifetime and high throughput, increases. Mobility of devices either in terms of mobile nodes or mobile sinks is a promising solution that can assist, for example, topology control and congestion mitigation. Such factors significantly contribute to the extension of the lifetime and the throughput of wireless ad-hoc networks. In this work we review and classify algorithms that introduce the characteristic of mobility in WSNs. We consider WSNs to be bo...

This study gives a simple introduction to WSNs architecture, potential topologies and measurement of physical parameters with crossbow tool.

The routing protocols are characterized into three main categories; localization-based, localization-free and cooperative schemes and the performance of these protocols are discussed with respect to various network parameters such as energy consumption, network lifetime, delay, reliability, and communication overheads.

The purpose of this article is to provide an up-to-date presentation of both traditional and most recent applications of Wireless Sensor Networks to enable the comprehension of this scientific area and facilitate the perception of novel applications.

This article presents a review of underwater routing protocols for UWSNs, and classify the existing underwater routing Protocols into three categories: energy-based, data- based, and geographic information-based protocols.

The use of WSN technology to control and manage irrigation systems is an ideal solution to ensure the efficient and rational use of water and thus contribute to reducing the severity of the global water crisis.

In this review, recent developments of ML techniques for WSNs are presented with much emphasis on DL techniques, and it is found that large training time and large dataset to get acceptable performance are accompanied with large energy consumption which is not favorable for resource-restrained W SNs.

The survey identifies often challenges and various significant issues that still essential to be addressed to develop a cost effective, efficient, long‐lasting, and almost maintenance‐free energy harvesting systems for WSNs along with trail to their possible solutions for future perspectives.

This work is intended to provide an introduction to EH technologies in terms of their general working principle, application potential, and other implementation considerations with the aim of accelerating the development of sustainable WSN applications in industry.

This paper has compared the performance of two nature-inspired optimization algorithms for getting optimal coverage in WSNs and observed that the optimal coverage is achieved at a lesser number of generations in LO as compared to IGA-BACA.

The LEACH-Fuzzy Clustering (LEACH-FC) protocol is proposed and the proposed algorithm has been found to be effective in balancing the energy load at each node thereby enhancing the reliability of WSN and outperforms other proposed algorithms for improving network lifetime and energy consumption.

The review work presented is categorized into energy management and renewable energy harvesting techniques, which discusses various methods to save energy consumption of the energy harvesting sensor networks and the different energy harvesting mechanisms, especially their protocol design strategies for maximizing energy harvesting.

This work derives the closed form expression for the optimization problem, corresponding to the energy efficiency and converts it to a parametric form, using Dinkelbach method and solves the new problem using Karush-Kuhn-Tucker (KKT) conditions.

The possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains is discussed, in addition to the challenges and proposed solutions to improving the ability of sensors to identify threats, attacks, risks, and malicious nodes through their ability to learn and self-development using machineLearning algorithms.

This paper has presented a systematic literature review of existing clone node detection schemes and provided the theoretical and analytical survey of the existing centralized and distributed schemes for the detection of clones in static WSNs with their drawbacks and challenges.

An improved version of grey wolf algorithm is proposed, that has been applied to improve the network lifetime optimization, and it is proven that the proposed metaheuristics performs better that other considered algorithms.

About 215 most important WSN clustering techniques are extracted, reviewed, categorized and classified based on clustering objectives and also the network properties such as mobility and heterogeneity, providing highly useful insights to the design of clustering Techniques in WSNs.

This paper reviews the literature with specific attention to aspects of wireless networking for the preservation of energy and aggregation of data in IoT-WSN systems.

This study emphasizes a comprehensive, future-oriented approach, delving into IoT-WSNs, wireless network protocols, and their applications in agriculture since 2019, and addresses recent issues and challenges related to IoT-WSNs and proposes mitigation strategies.

Simulation results show that the proposed strategy can improve the freshness of information collected from all the SNs and can always strike a balance between theSNs’ uploading time and the UAV’s flight time in various scenarios.

This paper forms an Online Locally Weighted Projection Regression (OLWPR) for anomaly detection in Wireless Sensor Network and attains the detection rate of 86 percentage and very low error rate of only 16%.

To provide readers with an overview of reliable data collection techniques in UWSNs, this paper categorizes them according to their ability to enhance reliability at all the key stages of data collection.

The review primarily focuses on the recently used wireless data acquisition system and execution of AI resources for data prediction and data diagnosis in RCC buildings and bridges and indicates the lag in real-world execution of structural health monitoring technologies despite advances in academia.

A wireless sensor network of low-cost sensor nodes for soil moisture that can help farmers optimize the irrigation processes in precision agriculture and developed a specific communication protocol to improve the performance.

An ensemble learning-based lightweight technique called Extremely Randomized Trees or Extra-Trees-based detection scheme has the ability of robustness towards signal noise and strong reduction of bias and variance error and the performances were compared with those of the state-of-the-art machine learning algorithms.

This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications, with particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems.

This article develops a novel ARSH-FATI-based Cluster Head Selection (ARSH-fatI-CHS) algorithm integrated with a heuristic called novel ranked-based clustering (NRC) to reduce the communication energy consumption of the sensor nodes while efficiently enhancing LT of the network.

During the previous few years, Wireless Sensor Network (WSN) appears as an active research domain due to the wide use of this technology in several applications, such as military, health, automation, and so forth. WSN supervises physical attributes where human activity is difficult or impossible. The WSN is a set of multiple sensor nodes that are haphazardly deployed in a specific space. These nodes sense data and record values continuously and send these data to the Base Station (BS) through other sensor nodes. Several issues are encountered in the WSNs, including energy consumption, deployme...

A fresh three-factor authentication scheme providing session keys for WSNs, using NS-3 for simulation shows that the scheme can run in IoT environment normally and has practical perspective.

An improved version of the firefly algorithm has been applied to improve the network lifetime maximization and conducted simulations have proven that the proposed metaheuristic achieves better and more consistent performance than other algorithms.

Two emerging trends in IoT are reviewed: the combination of RFID and WSNs in order to exploit their advantages and complement their limitations, and wearable sensors, which enable new promising IoT applications.

This article investigates the various causes and consequences of node capture attacks, and classify them into ten different types in terms of the attack targets, adversary’s capabilities and vulnerabilities exploited, and conducts a large-scale comparative measurement of 61 representative user authentication schemes for WSNs under the extended evaluation criteria.

This paper demonstrates the system verification projects in Wuxi, Jiangsu Province and Lianxiangyuan Community in Beijing, which have been widely used nationwide and put forward an application system for monitoring, inspection, security, and interactive service of layered power transmission and distribution system.

The proposed system and methodology is effective in alerting forest fires with lower latency than the existing systems and to acquire more accurate fire detection, a machine learning regression model is proposed.

The objective, key features, shortcomings, and benefits of different clustering techniques are examined in this survey to provide a deeper insight of the clustering area to the researchers, which can help them in their new journey of research in this domain.

This algorithm aims to manage the consumption of energy by WS nodes and enhance the running time for WSN given space constraints and achieves uniform distribution in spatial domain of CH, which effectively balance the energy consumption.

A lightweight and reliable authentication protocol is proposed for WMSN, which is composed of cutting-edge blockchain technology and physically unclonable functions (PUFs) and a fuzzy extractor scheme is introduced to deal with biometric information.