資料傳輸網路之貝氏診斷; Bayesian Tomography for Data Routing Networks

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/7741

Title:	資料傳輸網路之貝氏診斷;Bayesian Tomography for Data Routing Networks
Authors:	賴昱瑋;Yu-wei Lai
Contributors:	統計研究所
Keywords:	服務品質;工作遺失率;資料傳輸網路;流量控制策略;quality of service;job loss rate;tree-type of data routing network model;flow control policy
Date:	2009-06-04
Issue Date:	2009-09-22 11:03:41 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	隨著現代化網路的快速擴張及普及化，網路使用者對於網路服務品質(quality of service；QoS)的要求也越來越高，而網路服務品質通常可藉由工作延遲(job delay)、工作遺失率(job loss rate)等系統表現值來衡量。本文探討一樹狀架構的資料傳輸網路(tree-type of data routing network)，並利用點對點(end-to-end)的部份資訊來偵測(或估計)網路連結的工作遺失率(通過率)。本文使用的方法是建立一個統計模型並藉由貝氏方法來解決此問題。最後，我們介紹如何藉由所得到之工作通過率估計值建構一最佳動態的流量控制策略(flow control policy)。 Assessing and monitoring the performance of computer and communications networks is an important problem for network engineers. We consider a tree-type of data routing network model, and it has a broad application in real life (public telephone switches, call centers, etc.). Our focus here is on estimating and monitoring network Quality-of-Service (QoS) parameters. The QoS of a network can usually be measured by some system performance such as job delay or job loss rate. In this article , We propose a Bayesian method for detect(or,say,estimate) the job loss rate of edge level parameters from end-to-end path-level measurements, an important engineering problem that raises interesting statistical modeling issues. Further, we introduce how we can use the estimated job loss rate to choose an optimal dynamic flow control policy.
Appears in Collections:	[Graduate Institute of Statistics] Electronic Thesis & Dissertation

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