Zikuan Liu, J. Almhana, V. Choulakian, R. McGorman
{"title":"Online optimal data transmission strategy under Markov channel","authors":"Zikuan Liu, J. Almhana, V. Choulakian, R. McGorman","doi":"10.1109/PERSER.2005.1506560","DOIUrl":null,"url":null,"abstract":"The challenges of providing data services over wireless networks come from, their high reliability requirement under noisy wireless channels. In this paper, we model the noisy channel by a continuous-time Markov process and propose a dynamical packet transmission strategy for data service. The transmission strategy optimization is formulated as a Markov decision process. We establish that the optimal strategy has a threshold structure and develop a single sample path-based optimization algorithm to tune the thresholds. Since only a single sample path is involved, the proposed algorithm can be implemented online.","PeriodicalId":375822,"journal":{"name":"ICPS '05. Proceedings. International Conference on Pervasive Services, 2005.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICPS '05. Proceedings. International Conference on Pervasive Services, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERSER.2005.1506560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The challenges of providing data services over wireless networks come from, their high reliability requirement under noisy wireless channels. In this paper, we model the noisy channel by a continuous-time Markov process and propose a dynamical packet transmission strategy for data service. The transmission strategy optimization is formulated as a Markov decision process. We establish that the optimal strategy has a threshold structure and develop a single sample path-based optimization algorithm to tune the thresholds. Since only a single sample path is involved, the proposed algorithm can be implemented online.