{"title":"Id3 Based Periodic Sampled Classifier Algorithm for The Enhancement of Routing Protocol in Wireless Sensor Networks","authors":"Francis Twinkle Graf, C. Arunachalaperumal","doi":"10.37896/pd91.4/91429","DOIUrl":null,"url":null,"abstract":"Routing protocols for a Wireless Sensor Network (WSN) accomplishes the data dissemination between sensor nodes by preferring the next best node in the routing path. Supervised machine learning comes up with many strategies which can upgrade this next node selection for the range of applications. In this paper, ID3 based next node selection algorithm which uses entropy values for path resumption has been proposed. The simulation study of the algorithm showed that it performs well when compared to k-Nearest Neighbour and Naive Bayes algorithms in terms of evaluation metrics obtained from the confusion matrix and F1-score.","PeriodicalId":20006,"journal":{"name":"Periodico Di Mineralogia","volume":"67 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Periodico Di Mineralogia","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.37896/pd91.4/91429","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Routing protocols for a Wireless Sensor Network (WSN) accomplishes the data dissemination between sensor nodes by preferring the next best node in the routing path. Supervised machine learning comes up with many strategies which can upgrade this next node selection for the range of applications. In this paper, ID3 based next node selection algorithm which uses entropy values for path resumption has been proposed. The simulation study of the algorithm showed that it performs well when compared to k-Nearest Neighbour and Naive Bayes algorithms in terms of evaluation metrics obtained from the confusion matrix and F1-score.
期刊介绍：
Periodico di Mineralogia is an international peer-reviewed Open Access journal publishing Research Articles, Letters and Reviews in Mineralogy, Crystallography, Geochemistry, Ore Deposits, Petrology, Volcanology and applied topics on Environment, Archaeometry and Cultural Heritage. The journal aims at encouraging scientists to publish their experimental and theoretical results in as much detail as possible. Accordingly, there is no restriction on article length. Additional data may be hosted on the web sites as Supplementary Information. The journal does not have article submission and processing charges. Colour is free of charges both on line and printed and no Open Access fees are requested. Short publication time is assured.
Periodico di Mineralogia is property of Sapienza Università di Roma and is published, both online and printed, three times a year.
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