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CNR:A Cluster-Based Solution for Connectivity Restoration for Mobile WSNs

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摘要 Wireless Sensor Networks(WSNs)are an integral part of the Internet of Things(IoT)and are widely used in a plethora of applications.Typically,sensor networks operate in harsh environments where human intervention is often restricted,which makes battery replacement for sensor nodes impractical.Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network.Without a connectivity restoration mechanism,node failures ultimately lead to a network partition,which affects the basic function of the sensor network.Therefore,the research community actively concentrates on addressing and solving the challenges associated with connectivity restoration in sensor networks.Since energy is a scarce resource in sensor networks,it becomes the focus of research,and researchers strive to propose new solutions that are energy efficient.The common issue that is well studied and considered is how to increase the network’s life span by solving the node failure problem and achieving efficient energy utilization.This paper introduces a Clusterbased Node Recovery(CNR)connectivity restoration mechanism based on the concept of clustering.Clustering is a well-known mechanism in sensor networks,and it is known for its energy-efficient operation and scalability.The proposed technique utilizes a distributed cluster-based approach to identify the failed nodes,while Cluster Heads(CHs)play a significant role in the restoration of connectivity.Extensive simulations were conducted to evaluate the performance of the proposed technique and compare it with the existing techniques.The simulation results show that the proposed technique efficiently addresses node failure and restores connectivity by moving fewer nodes than other existing connectivity restoration mechanisms.The proposed mechanism also yields an improved field coverage as well as a lesser number of packets exchanged as compared to existing state-of-the-art mechanisms.
出处 《Computers, Materials & Continua》 SCIE EI 2021年第12期3413-3427,共15页 计算机、材料和连续体(英文)
基金 This research is funded by Najran University Saudi Arabia,under the research Project Number(NU/ESCI/17/093).URL:www.nu.edu.sa。
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