{"title":"基于多级II型模糊逻辑的无线传感器网络连通性预测","authors":"Anvita, I. Snigdh","doi":"10.1109/ICICT48043.2020.9112497","DOIUrl":null,"url":null,"abstract":"Topology, whether fixed or ad hoc is dependent on the availability of a connection between the nodes as well as the stability of the connection. The agricultural monitoring scenario uses inadvertently an ad hoc and randomly places sensor nodes. Therefore, the three factors; availability, stability and connectivity become major parameters to determine the health of the network. Our paper tires to predict the stability and availability of the routes by employing fuzzy inference system at the sink node. During analysis we also observe that the dependence and computations of the aforementioned parameters are multi-faceted and hence one FIS could not accurately interpret the dependence of such factors on the network. Therefore, based on the characteristics of the factors we design a multi-level type I and type II fuzzy system to predict connectivity of a WSN network.","PeriodicalId":408134,"journal":{"name":"2020 International Conference on Inventive Computation Technologies (ICICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Multi-Level Type II Fuzzy Logic based Prediction of Connectivity in a Wireless Sensor Network\",\"authors\":\"Anvita, I. Snigdh\",\"doi\":\"10.1109/ICICT48043.2020.9112497\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Topology, whether fixed or ad hoc is dependent on the availability of a connection between the nodes as well as the stability of the connection. The agricultural monitoring scenario uses inadvertently an ad hoc and randomly places sensor nodes. Therefore, the three factors; availability, stability and connectivity become major parameters to determine the health of the network. Our paper tires to predict the stability and availability of the routes by employing fuzzy inference system at the sink node. During analysis we also observe that the dependence and computations of the aforementioned parameters are multi-faceted and hence one FIS could not accurately interpret the dependence of such factors on the network. Therefore, based on the characteristics of the factors we design a multi-level type I and type II fuzzy system to predict connectivity of a WSN network.\",\"PeriodicalId\":408134,\"journal\":{\"name\":\"2020 International Conference on Inventive Computation Technologies (ICICT)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Inventive Computation Technologies (ICICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICT48043.2020.9112497\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Inventive Computation Technologies (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT48043.2020.9112497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Level Type II Fuzzy Logic based Prediction of Connectivity in a Wireless Sensor Network
Topology, whether fixed or ad hoc is dependent on the availability of a connection between the nodes as well as the stability of the connection. The agricultural monitoring scenario uses inadvertently an ad hoc and randomly places sensor nodes. Therefore, the three factors; availability, stability and connectivity become major parameters to determine the health of the network. Our paper tires to predict the stability and availability of the routes by employing fuzzy inference system at the sink node. During analysis we also observe that the dependence and computations of the aforementioned parameters are multi-faceted and hence one FIS could not accurately interpret the dependence of such factors on the network. Therefore, based on the characteristics of the factors we design a multi-level type I and type II fuzzy system to predict connectivity of a WSN network.