{"title":"Bio-inspired routing protocol for wireless sensor network to minimise the energy consumption","authors":"Padmalaya Nayak, Ch Praneeth Reddy","doi":"10.1049/iet-wss.2019.0198","DOIUrl":null,"url":null,"abstract":"<div>\n <p>The minimisation of energy consumption has become an emerging topic in wireless sensor networks (WSNs) as these networks enable a wealth of new applications. The internet of things (IoT) application is one of them and the current hype around the IoT is huge. Therefore, the development of efficient communication protocols for WSNs is a major concern. In this context, various research communities have triggered several optimisation techniques to provide energy-efficient solutions to WSNs. This study aims to apply the genetic algorithm (GA) in WSNs clustering and to evaluate its performance over another optimisation technique. The proposed protocol is analytically analysed and compared with a fuzzy logic (FL)-based routing protocol and traditional routing protocol like LEACH and <i>K</i>-means using a Java-based custom simulator. Simulation results show that there is a trade-off between GA-clustering and FL-clustering, but the overall performance of GA-clustering is very promising for obtaining optimal energy consumption.</p>\n </div>","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1049/iet-wss.2019.0198","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Wireless Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/iet-wss.2019.0198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 7
Abstract
The minimisation of energy consumption has become an emerging topic in wireless sensor networks (WSNs) as these networks enable a wealth of new applications. The internet of things (IoT) application is one of them and the current hype around the IoT is huge. Therefore, the development of efficient communication protocols for WSNs is a major concern. In this context, various research communities have triggered several optimisation techniques to provide energy-efficient solutions to WSNs. This study aims to apply the genetic algorithm (GA) in WSNs clustering and to evaluate its performance over another optimisation technique. The proposed protocol is analytically analysed and compared with a fuzzy logic (FL)-based routing protocol and traditional routing protocol like LEACH and K-means using a Java-based custom simulator. Simulation results show that there is a trade-off between GA-clustering and FL-clustering, but the overall performance of GA-clustering is very promising for obtaining optimal energy consumption.
期刊介绍:
IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.