{"title":"基于策略的网络管理中的自治","authors":"M. Siddiqui, C. Hong, Mi-Jung Choi","doi":"10.1109/NOMS.2012.6212046","DOIUrl":null,"url":null,"abstract":"In this paper, we have devised a reinforcement learning algorithm, which helps in enabling autonomic control loops in Policy based Autonomic Network Management (PBANM). We have proposed two autonomic control loops for optimal configuration and policy optimization in PBANM system. Simulations are performed to validate our proposal.","PeriodicalId":364494,"journal":{"name":"2012 IEEE Network Operations and Management Symposium","volume":"8 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Autonomies in policy based network management\",\"authors\":\"M. Siddiqui, C. Hong, Mi-Jung Choi\",\"doi\":\"10.1109/NOMS.2012.6212046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we have devised a reinforcement learning algorithm, which helps in enabling autonomic control loops in Policy based Autonomic Network Management (PBANM). We have proposed two autonomic control loops for optimal configuration and policy optimization in PBANM system. Simulations are performed to validate our proposal.\",\"PeriodicalId\":364494,\"journal\":{\"name\":\"2012 IEEE Network Operations and Management Symposium\",\"volume\":\"8 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Network Operations and Management Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NOMS.2012.6212046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Network Operations and Management Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NOMS.2012.6212046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we have devised a reinforcement learning algorithm, which helps in enabling autonomic control loops in Policy based Autonomic Network Management (PBANM). We have proposed two autonomic control loops for optimal configuration and policy optimization in PBANM system. Simulations are performed to validate our proposal.
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