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研究生： Peter Gerhat
Peter - Gerhat
論文名稱： EFT交換器節點選擇之模糊推論系統
Fuzzy Algorithm for EFT Switch Node Selection
指導教授： 歐陽超
Chao Ou-Yang
口試委員: 阮業春
Yeh-Chun Juan
羅士哲
Shih-Che Lo
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理系
Department of Industrial Management
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 89
中文關鍵詞： 電子資金轉帳 、績效評估 、路由演算法 、模糊邏輯
外文關鍵詞： Electronic funds transfer, Performance evaluation, Routing algorithms, Fuzzy Logic
相關次數： 點閱：175  下載：4 
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    • 即時系統需要用建模與模擬來當作其重要衡量指標，諸如它的回應時效和處理能力等。電子資金轉帳系統在每秒內需處理大量的交易，任何當機的狀況發生對業務的影響均非常巨大，然而目前的資料交換系統易產生效能障礙與缺少資料運算來源，其中最重要的工作之一是資料交換路由，當資料交換時必須由一個網絡節點到另一個節點，為了盡量減少每個節點的佇列長度與提高系統整體效能，本研究提供一個最優化的路由選擇的運算方法。另運用模糊方式而捨棄分析方法，這是基於複雜的數學公式的運算，易產生較大的計算負擔。再者本研究選擇節點效能、安全性與可靠度以作為決策標準。最後我們模擬各種情況下實際工作量用隨機虛擬數據加以測試。

    Real-time systems require modeling and simulation to evaluate important performance measures such as response time and throughput. Electronic Funds Transfer systems process large amounts of transactions in each second and any downtime could have very negative impact on business. The systems are especially vulnerable to performance bottlenecks and lack of computational resources. One of the most critical tasks is transaction routing, when transactions have to be routed from one network node to another. In order to minimize the queue lengths for each node and improve overall system performance an efficient algorithm has to be chosen to determine the most optimal routing option. The fuzzy approach performs better in comparison to analytical methods, which are based on complex mathematical formulas and would present a large computational overhead. Node performance, security and reliability were chosen as decision criteria. The algorithm was tested with pseudo-random data under various scenarios representing actual workloads.

    Chapter 1: Introduction 1 1.1 Electronic Funds Transfer 1 1.2 Current Algorithm 4 1.3 Research Goals 6 Chapter 2: Background 8 2.1 EFT Systems 8 2.2 Routing 10 2.3 Fuzzy Routing 10 2.4 Software Performance Models 13 2.5 Network Performance 15 2.6 Network Security 16 Chapter 3: Proposed Approach 18 3.1 Research Framework 18 3.2 Algorithm Overview 19 3.3 BIN Routing 26 3.4 Static Fuzzy Routing 28 3.5 Dynamic Fuzzy Routing 29 3.6 Queue Rating 31 3.7 Performance Rating 32 3.8 User Rating 37 3.9 Security Rating 38 3.10 Reliability Rating 39 3.12 Simulator 41 3.13 Modeling Language 43 Chapter 4: Experimental Results 50 4.1 Experimental Design 50 4.2 Performance Experiments 53 4.3 Fuzzy Experiments 57 Chapter 5: Conclusions 63 5.1 Conclusion 63 5.2 Future Work 64 References 66 Appendix A 69 Appendix B 72 Appendix C 74 Appendix D 78 Appendix E 80

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