臺灣博碩士論文加值系統

隨著時代的演變，行動裝置的興起，無線網路架構儼然是一種新的趨勢，但無線網路最為人所詬病的舊是安全性以及穩定性的問題，所以本研究針對大規模分散式的無線網路提出一種新的演算法，能夠針對以下狀況給予因應：1)節點數量且網路範圍廣泛，本研究針對所能夠支援的網路節點約為10萬個；2)可以針對網路流動率高的情況，在本研究中我們會針對流失率高的網站提出因應措施，讓網路仍舊保持高搜尋成功率；3)針對網路的惡意攻擊，我們也提出因應措施，即使網路在不安全的情況下仍舊保持高搜尋成功率；4)自我適應機制，本研究的演算法會針對網路情況的變化而改變我們的行為，進而有效的降低網路運行成本，兼具高效能與低成本的特性。
分散式的無線網路最容易產生的問題就是安全性，本研究針對此部分提出一個解決方案，首先我們修正了許多過往研究所提出的網路模型，整理出一個適合大規模無線網路情況的網路運行模式，接著針對網路的攻擊的部分，我們透過對每次搜尋結果所產生得資訊，與我們預先分析出來的預期結果進行分析，比對出目前網路的情況，根據該情況去調整搜尋發送的數量，來維持網路的高搜尋成功率。
本研究也將所提出的演算法與其他演算法進行比對，在相同的系統環境下，我們模擬具有龐大數量節點的大規模的無線網路，並且針對其耗費的成本以及搜尋成功率進行比較以及研究，結果證實，我們的演算法在耗費成本以及整體效能的平衡的表現最為優秀。

In this study, we want to propose a new algorithm for large-scale distributed wireless networks, which can be applied to the following conditions: 1) The number of nodes and the wide range of networks, this study is based on supporting the network node is up to 100,000 ; 2) In the high rate of network flow, we will respond to the high rate in this study, so that the network will still maintain a high match probability; 3) We also responded to the malicious attacks on the network, even if the network is still maintain a high match probability; 4) self-adaptation mechanism, our algorithm will change behavior when the network changes, and thus effectively reducing the network operating costs, both high-performance and low-cost characteristics.

The most likely problem with Large & Mobile Wireless Network is security. This study presents a solution to this. First, we have revised many of the network models proposed by the previous research to address a situation suitable for large-scale wireless networks. Then, we have modified many of the networks proposed by our past studies. We sort out a suitable scenario for large-scale wireless network of the network mode to operate properly. Then for the network attacks, we have generated information on each search result. After analyzing this information with our pre-determined results, we compared this information with the current network situation, and then adjust the number of request to maintain the high match probability.
 
This study also compares the proposed algorithm with other algorithms. In the same system environment, we simulate a large-scale wireless network with a large number of nodes, and then compare distribution cost and the search cost and research. The results confirm that our algorithm requires low costs but can still achieve high match probability.

第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 5
1.3 預期成果與貢獻 6
第二章 文獻探討 7
2.1 對等式網路中的分散式搜尋(Distribution search in Peer-to-Peer) 7
2.2 無線感測網路(WSN)和隨建即連網路(MANET) 10
2.3 移動指數加權平均(EWMA)和卡方統計(Chi-Squared Statistic) 12
2.4 防止惡意攻擊 13
2.5 防止選擇性轉發攻擊 14
2.6 區域敏感雜湊函數 15
第三章 研究方法 16
3.1 MSLM系統流程 17
3.2 節點類型 19
3.3 加入區域 21
3.4 離開區域 20
3.5 發佈詮譯資料 21
3.6 發佈查詢訊息 25
3.7 中繼節點 27
3.8 分割文檔(Shingling of Documents) 28
3.9 杰卡德相似度(Jaccard Similarity)與k-grams 29
3.10 最小化雜湊(Minhashing) 29
3.11 區域敏感雜湊函數(Locality Sensitive Hash ,LSH) 32
3.12 以概率密度函數(Probability Density Function)進行分析 33
3.13 訊息轉發的配對率(Match Probabilities With Message Forwarding) 34
3.14 指數加權移動平均法(Exponential Weighted Moving Average Method) 36
3.15 正規化(Normalization) 37
3.16 修正卡方統計(Modified Chi-Square) 38
第四章 實驗結果與分析 39
4.1 實驗環境 39
4.2 實驗變數 40
4.3 評估指標 42
4.4 實驗結果 43
4.4.1 搜尋成功率 43
4.4.2 訊息成本 46
4.4.3 研究實驗總結 48
第五章 研究結論與未來方向 49
5.1 研究結論 49
5.2 未來方向與建議 50
參考文獻 51

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