{"title":"Buffer Optimal Control Algorithm for Broadband Satellite Networks","authors":"He Ning, Wang Lei","doi":"10.1109/CMC.2010.341","DOIUrl":null,"url":null,"abstract":"To solve the buffer management problem in Broadband satellite Networks, based on the IPA (Infinitesimal Perturbation Analysis) method, a new algorithm was proposed. The algorithm regarded the buffer management problem as one minimization of the performance function with the decision variable (specially, the buffer threshold) describing the nod with SFM (Stochastic Fluid Model). IPA technique was used to derive sensitivity estimators for the performance function, thus provided SA (Stochastic Approximation) algorithms capable to optimally minimize the performance cost based on IPA gradient. The algorithm can be evaluated based on data observed from the sample path of the real system without any pre-knowledge of the inflow.","PeriodicalId":296445,"journal":{"name":"2010 International Conference on Communications and Mobile Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Communications and Mobile Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMC.2010.341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To solve the buffer management problem in Broadband satellite Networks, based on the IPA (Infinitesimal Perturbation Analysis) method, a new algorithm was proposed. The algorithm regarded the buffer management problem as one minimization of the performance function with the decision variable (specially, the buffer threshold) describing the nod with SFM (Stochastic Fluid Model). IPA technique was used to derive sensitivity estimators for the performance function, thus provided SA (Stochastic Approximation) algorithms capable to optimally minimize the performance cost based on IPA gradient. The algorithm can be evaluated based on data observed from the sample path of the real system without any pre-knowledge of the inflow.