跳到主要內容

簡易檢索 / 詳目顯示

回結果列表
研究生： 金立人
Chin, Li-Jen
論文名稱： 數位網路上預算的二階段配置法
A Two-Phase Approach on Budget Allocation for All-IP Networks
指導教授： 陸行
Luh,H.
學位類別： 碩士
Master
系所名稱： 理學院 - 應用數學系
Department of Mathematical Sciences
論文出版年： 2005
畢業學年度： 93
語文別： 英文
論文頁數： 62
中文關鍵詞： All-IP網路 、資源分配
外文關鍵詞： All-IP Networks, Resource Allocation
相關次數： 點閱：84  下載：37 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 本論文著眼於All-IP網路中的預算分配。我們定義網路的服務品質只與各使用者使用網路頻寬的要求有關，提出一種使管理者能以統計上百分比來估計網路服務品質的方法。這個方法包含路徑選擇以及頻寬分配二個階段。為了展現這種方法的可行性，我們列舉一些數據來分別比較以最大滿意度和最小成本為目標的不同分配結果，作為使用這個方法的參考。

    In this thesis, we focus on budget allocation for All-IP networks. We propose a method which assists managers to estimate the quality of service on networks. The quality of service on networks is defined by satisfaction functions that are simply written in terms of bandwidth required by the users on the network. We present a two-phase approach which includes a path se-lection and a scheme for bandwidth allocation. In order to illustrate an easy implementation of this approach, we also develop the Maximum Satisfaction Method and the Minimum Cost Method. Numerical examples are given to show the effectiveness of our approach.

    Abstract (in Chinese) I
    Abstract II
    1. Introduction 1
    2. The Maximum Satisfaction Method 7
    2.1 The Two Phases: MBM and BRAM 7
    2.2 Example 1 of MBM Model 12
    2.3 Example 1 of BRAM Model with 15
    2.3.1 Calculate the satisfaction by the expected number of
    connections 15
    2.3.2 Simulation of example 1 with the same weights 17
    2.4 Example 1 of BRAM model with different weights 18
    2.4.1 Calculate the satisfaction by the expected number of
    connections 18
    2.4.2 Simulation of example 1 with different weights 19
    2.5 Example 2 with MBM Model 19
    2.5.1 Three classes have different weights 21
    2.5.2 Simulation of example 2 22
    2.6 The Application on another All-IP Network 23
    2.6.1 Calculate the satisfaction with the expected number of
    connections 26
    2.6.2 Simulation 27
    3. The Minimum Cost Method 28
    3.1 A Simulation Algorithm Applied on All-IP Networks 28
    3.1.1 A Statistical inference process of our study 32
    3.1.2 The simulation process 33
    3.2 The Minimum Cost Method 36
    3.2.1 Example 1 of MCM model 36
    3.2.2 Example 1 of MCM with 38
    3.2.3 Three classes with different weights 39
    3.3 Example 2 of MCM Model 40
    3.4 The Application on another All-IP Network 44
    4. Comparison of Maximum Satisfaction Method with the Minimum
    Cost Method 49
    4.1 Comparison by examples 49
    4.2 Another Network 51
    5. Conclusion 55
    Bibliography 57

    [1] P.J. Bickel and K.A. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics, Prentice Hall, 1977.
    [2] J. Boyle, RSVP Extensions for CIDR Aggregated Data Flow, Internet work in progress, June 1997.
    [3] K. Gopalan and T. Chiueh, Delay Budget Allocation in Dlay Bounded Network Paths, Technical Report TR-113, Experimental Computer Sys-tems Labs, Dept. of Computer Science, State University of New York, Stony Brook, NY, June 2002.
    [4] D. Mitra and Q. Wang, Stochastic Traffic Engineering, with Applications to Network Revenue Management, Proceedings of IEEE INFOCOM'03, San Francisco, 2-10, CA, 2003.
    [5] MATLAB 6.5, the Mathworks, Inc., 2002.
    [6] E. Mulyana, U. Killat, A Hybrid Genetic Algorithm Approach for OSPF Weight Setting Problem, 2nd POLISH-GERMAN TELETRAFFIC SYM-POSIUM PGTS, 9th Polish Teletraffic Symposium, 2002, found in inter-net.
    [7] E. Mulyana and U. Killat, An Alternative Genetic Algorithm to Optimize OSPF Weights, July 2002, found in internet.
    [8] W. Ogryczak, T. Śliwiński and A. Wierzbicki, Fair Resource Allocation Schemes and Network Dimensioning Problems, Journal of Telecommu-nication and Information Technology, 34-42, Mar. 2003.
    [9] A. Orda, Routing with End-to-End QoS Guarantees in Broadband Net-works, IEEE/ACM Transaction on Networking, Vol. 7, No. 3, 365-374, June 1999.
    [10] K.G. Ramakrishnan and M.A. Rodrigues, Optimal Routing in Shortest Path Data Networks, Bell Labs Technical Journal, 117–138, January, June 2001.
    [11] S. Rooney, Connection closures: Adding application-defined behavior to network connections, Internet work in progress, April 1997.
    [12] P. Thomas, D. Teneketzis, J. K. Mackie-Mason, A Market-Based Ap-proach to Optimal Resource Allocation in Integrated-Services Connec-tion-Oriented Networks, Operations Research, Vol. 50, No. 4, 603-616, July-August 2002.
    [13] C.H. Wang, Mathematical Models of Pareto Optimal Path Selection on All-IP Networks, Master Thesis, National Chengchi University, Taipei, 2004.
    [14] L. W. Winston, Operations Research Applications and Algorithms, Bel-mont, CA: THOMSON BROOKS/COLE, 2004.

    QR CODE
    :::