{"title":"机器学习在自组织无线网络配置管理中的作用","authors":"Sung-eok Jeon, C. Ji","doi":"10.1145/1080173.1080191","DOIUrl":null,"url":null,"abstract":"In this work, we show that machine learning, e.g., graphical models, plays an important role for the self-configuration of ad hoc wireless network. The role of such a learning approach includes a simple representation of complex dependencies in the network and a distributed algorithm which can adaptively find a nearly optimal configuration.","PeriodicalId":216113,"journal":{"name":"Annual ACM Workshop on Mining Network Data","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Role of machine learning in configuration management of ad hoc wireless networks\",\"authors\":\"Sung-eok Jeon, C. Ji\",\"doi\":\"10.1145/1080173.1080191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we show that machine learning, e.g., graphical models, plays an important role for the self-configuration of ad hoc wireless network. The role of such a learning approach includes a simple representation of complex dependencies in the network and a distributed algorithm which can adaptively find a nearly optimal configuration.\",\"PeriodicalId\":216113,\"journal\":{\"name\":\"Annual ACM Workshop on Mining Network Data\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual ACM Workshop on Mining Network Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1080173.1080191\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual ACM Workshop on Mining Network Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1080173.1080191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Role of machine learning in configuration management of ad hoc wireless networks
In this work, we show that machine learning, e.g., graphical models, plays an important role for the self-configuration of ad hoc wireless network. The role of such a learning approach includes a simple representation of complex dependencies in the network and a distributed algorithm which can adaptively find a nearly optimal configuration.
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