Dhouha El Houssaini, Zaid Abdullah, Sabrine Kheriji, K. Besbes, O. Kanoun
{"title":"基于多元线性回归的距离定位算法评价准则设计","authors":"Dhouha El Houssaini, Zaid Abdullah, Sabrine Kheriji, K. Besbes, O. Kanoun","doi":"10.5220/0011013100003118","DOIUrl":null,"url":null,"abstract":"Localization is an essential feature in numerous Wireless Sensor Network (WSN) applications, including tracking, health monitoring, and military supervision. Analytical modeling and analysis of the localization system remain challenging and infeasible since it offers oversimplified results with limited reliability to the evaluated cases. Likewise, disseminating test-beds involves a lot of effort, making the simulation phase indispensable to study the WSN localization. The defined localization model needs to ensure solid and pragmatic network assumptions during the simulation. However, most network simulators don’t meet specific criteria related to network definition, such as scalability and heterogeneity. As part of this endeavor, a guideline for evaluating and analyzing technical methods of range-based localization is developed. Multiple linear regression is used to generate the different localization instances, which enables to support different and non-dependent parameters. The developed guideline for range-based localization is tested and validated for existing localization","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"87 1","pages":"256-262"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Design of a Guideline for Range-based Localization Algorithms Evaluation using Multiple Linear Regressions\",\"authors\":\"Dhouha El Houssaini, Zaid Abdullah, Sabrine Kheriji, K. Besbes, O. Kanoun\",\"doi\":\"10.5220/0011013100003118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Localization is an essential feature in numerous Wireless Sensor Network (WSN) applications, including tracking, health monitoring, and military supervision. Analytical modeling and analysis of the localization system remain challenging and infeasible since it offers oversimplified results with limited reliability to the evaluated cases. Likewise, disseminating test-beds involves a lot of effort, making the simulation phase indispensable to study the WSN localization. The defined localization model needs to ensure solid and pragmatic network assumptions during the simulation. However, most network simulators don’t meet specific criteria related to network definition, such as scalability and heterogeneity. As part of this endeavor, a guideline for evaluating and analyzing technical methods of range-based localization is developed. Multiple linear regression is used to generate the different localization instances, which enables to support different and non-dependent parameters. The developed guideline for range-based localization is tested and validated for existing localization\",\"PeriodicalId\":72028,\"journal\":{\"name\":\"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks\",\"volume\":\"87 1\",\"pages\":\"256-262\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0011013100003118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0011013100003118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of a Guideline for Range-based Localization Algorithms Evaluation using Multiple Linear Regressions
Localization is an essential feature in numerous Wireless Sensor Network (WSN) applications, including tracking, health monitoring, and military supervision. Analytical modeling and analysis of the localization system remain challenging and infeasible since it offers oversimplified results with limited reliability to the evaluated cases. Likewise, disseminating test-beds involves a lot of effort, making the simulation phase indispensable to study the WSN localization. The defined localization model needs to ensure solid and pragmatic network assumptions during the simulation. However, most network simulators don’t meet specific criteria related to network definition, such as scalability and heterogeneity. As part of this endeavor, a guideline for evaluating and analyzing technical methods of range-based localization is developed. Multiple linear regression is used to generate the different localization instances, which enables to support different and non-dependent parameters. The developed guideline for range-based localization is tested and validated for existing localization