Effective Bandwidth Estimation in Data Networks: An Analysis for Two Traffic Characterizations
作者机构:Departamento de MatemáticaUniversidad Nacional del SurAv.Alem 1253Bahía Blanca8000Argentina
出 版 物:《Electrical Science & Engineering》 (电气科学与工程(英文))
年 卷 期:2021年第3卷第1期
页 面:23-29页
学科分类:07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题:Effective bandwidth Markov fluid model Kernel estimation Data networking Monte Carlo Markov Chain algorithms
摘 要:The Generalized Markov Fluid Model(GMFM)is assumed for modeling sources in the network because it is versatile to describe the traffic *** order to estimate resources allocations or in other words the channel occupation of each source,the concept of effective bandwidth(EB)proposed by Kelly is *** this paper we use an expression to determine the EB for this model which is of particular interest because it allows expressing said magnitude depending on the parameters of the *** paper provides EB estimates for this model applying Kernel Estimation techniques in data *** particular we will study two differentiated cases:dispatches following a Gaussian and Exponential *** performance of the proposed method is analyzed using simulated traffic traces generated by Monte Carlo Markov Chain *** estimation process worked much better in the Gaussian distribution case than in the Exponential one.