{"title":"移动网络在三维空间中的时间函数预测:一个框架","authors":"M. Al-Hattab, Nuha Hamada","doi":"10.1109/ACIT47987.2019.8991022","DOIUrl":null,"url":null,"abstract":"Mobility prediction has attracted increasing interest in recent years, as correct and accurate prediction can lead to efficient data delivery and provide the user with high quality of service. Moreover, it enables the network to plan for future tasks in the suitable time. In this paper, we present a framework for a prediction scheme that predict the future mobility of mobile networks in three-dimensional space using polynomial regression and provide a time-space mapping to produce a time function for the three components of the trajectory for the node","PeriodicalId":314091,"journal":{"name":"2019 International Arab Conference on Information Technology (ACIT)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Mobility prediction as a time function for mobile networks in 3-D space: A Framework\",\"authors\":\"M. Al-Hattab, Nuha Hamada\",\"doi\":\"10.1109/ACIT47987.2019.8991022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobility prediction has attracted increasing interest in recent years, as correct and accurate prediction can lead to efficient data delivery and provide the user with high quality of service. Moreover, it enables the network to plan for future tasks in the suitable time. In this paper, we present a framework for a prediction scheme that predict the future mobility of mobile networks in three-dimensional space using polynomial regression and provide a time-space mapping to produce a time function for the three components of the trajectory for the node\",\"PeriodicalId\":314091,\"journal\":{\"name\":\"2019 International Arab Conference on Information Technology (ACIT)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Arab Conference on Information Technology (ACIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACIT47987.2019.8991022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Arab Conference on Information Technology (ACIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACIT47987.2019.8991022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobility prediction as a time function for mobile networks in 3-D space: A Framework
Mobility prediction has attracted increasing interest in recent years, as correct and accurate prediction can lead to efficient data delivery and provide the user with high quality of service. Moreover, it enables the network to plan for future tasks in the suitable time. In this paper, we present a framework for a prediction scheme that predict the future mobility of mobile networks in three-dimensional space using polynomial regression and provide a time-space mapping to produce a time function for the three components of the trajectory for the node