Litcius/Paper detail

Energy-Efficient Routing Protocol Based on Multi-Threshold Segmentation in Wireless Sensors Networks for Precision Agriculture

Yindi Yao, Xiong Li, Yanpeng Cui, Jia-Jun Wang, Chen Wang

2022IEEE Sensors Journal73 citationsDOIOpen Access PDF

Abstract

Wireless sensor networks (WSNs), one of the fundamental technologies of the Internet of Things (IoT), can provide sensing and communication services efficiently for IoT-based applications, especially energy-limited applications. Clustering routing protocol plays an important role in reducing energy consumption and prolonging network lifetime. The cluster formation and cluster head selection are the key to improving the performance of the clustering routing protocol. An energy-efficient routing protocol based on multi-threshold segmentation (EERPMS) was proposed in this paper to improve the rationality of the cluster formation and cluster heads selection. In the stage of cluster formation, inspired by multi-threshold image segmentation, an innovative node clustering algorithm was developed. In the stage of cluster heads selection, aiming at minimizing the network energy consumption, a calculation theory of the optimal number and location of cluster heads was established. Furthermore, a novel cluster head selection algorithm was constructed based on the residual energy and optimal location of cluster heads. Simulation results show that EERPMS can improve the distribution uniformity of cluster heads, prolong the network lifetime and save up to 64.50%, 58.60% and 56.15% network energy as compared to RLEACH, CRPFCM and FIGWO protocols respectively.

Topics & Concepts

Computer scienceRouting protocolCluster analysisComputer networkWireless sensor networkEnergy consumptionNode (physics)Path vector protocolRouting (electronic design automation)Distributed computingReal-time computingWireless Routing ProtocolEngineeringArtificial intelligenceStructural engineeringElectrical engineeringEnergy Efficient Wireless Sensor NetworksSmart Agriculture and AIWater Quality Monitoring Technologies