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研究生:許家豪
研究生(外文):Chia-Hao Hsu
論文名稱:P2P資源分享系統中支援動態存取資源策略之名聲機制
論文名稱(外文):A Study on the Reputation Mechanism based on Dynamic Access Resources Strategies in P2P File Sharing Systems
指導教授:邵敏華邵敏華引用關係
指導教授(外文):Min-Hua Shao
學位類別:碩士
校院名稱:國立屏東科技大學
系所名稱:資訊管理系所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:57
中文關鍵詞:搭便車評價回饋名聲值管理
外文關鍵詞:Free-riderAppreciation FeedbackReputation Management
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點對點網路系統(Peer-to-Peer,以下簡稱P2P)利用節點間彼此的直接互動來進行電腦資源和服務的分享,提供一個檔案分享交流的平台。但在享受資源分享的同時,卻也產生了一些問題,如檔案不正確或是出現只下載資源卻不分享資源的人(即為free-riders)。為了能確保可以下載到品質良好的資源與解決free-riding的問題,許多研究文獻提出「名聲機制」來量化使用者的行為,藉由名聲機制來協助使用者在選擇下載資源時能有個參考依據,降低存取到不良檔案的情形。
有些名聲機制的名聲值計算是以「提供資源量」為主,若提供資源量愈多名聲值就愈高,名聲值高能存取的資源也就愈多。這樣的機制雖有激勵使用者分享資源的動機,但卻不能確保檔案資源的品質。另外有些名聲值計算是以「提供評價回饋」為主,針對下載資源給予評價回饋,這樣的機制可降低品質不良的檔案,但卻無法避免free-riders情形發生而且每位使用者的評價回饋都必須是誠實的。
為了考量檔案資源的品質、不實的評價回饋與free-riding的問題發生,本研究將提出適宜的名聲機制來解決這些問題。而此機制包含三個部份,第一部分是「動態存取資源策略」,根據使用者本身名聲值去劃分相對應的資源存取層級,該策略不僅提供激勵的效果並有效降低free-riders的問題外,也讓使用者在存取資源上更具有彈性,使用者能夠存取的資源範圍取決於本身名聲值多寡。然而名聲值相近的節點可能會產生一些惡意行為(如不實的評價回饋),為了避免這樣的情形發生,本機制的第二部分「評價回饋有效策略」因應而生。該策略是防止過多不實的評價對資源提供造成影響。最後一部分是「節點名聲值管理」,將使用者在網路上的行為予以量化,以提供「動態資源存取策略」與「評價回饋有效策略」衡量依據之用。
在模擬實驗結果中可發現,本研究的名聲機制確實可根據提供者傳送優劣檔案行為程度與使用者給予真實評價程度的不同予以區別,表示本研究的機制可依使用者的行為表現不同來區分各行為類型的使用者。而在本研究所提出三種劃分層級的基準,根據模擬結果顯示以「下限值」劃分基準效果較佳。除此之外,本研究與其他資源存取策略相互比較,結果顯示本研究的效能比「隨機資源存取」與「靜態層級資源存取」佳。
Peer-to-Peer (P2P) systems that nodes interact directly to share resources and services provide a kind platform of file sharing. Although P2P systems are convenient for getting resources, there are some problems such as inauthentic files or free-rider. In order to download good resources or solve free-riding, many researches provide “Reputation Mechanism” to quantify their behavior. It can assist us in having the references when we are going to download files and reduce the probability of accessing bad files.
A few reputation computing of the mechanisms are based on “amount of resources contribution”. The more they provided the more reputation value they have. Then they can access more resources. Such mechanisms can animate users to share files but they can not ensure the quality of resources. Others are based on “appreciation feedback”. They give some appreciations depending on the files which they downloaded. Such mechanisms can reduce the quantity of bad files. But it can not avoid the free-rider and it have to assume every appreciation is true.
In order to consider the quality of the resources, inauthentic feedback and free-riding, we propose a new mechanism to solve these questions. This mechanism includes three parts. The first part is called “The policy of dynamic accessing files”. It can not only provide the simulative effect to reduce the problem about free-rider but also provide the flexibility of accessing files for users. Users who can access resources range depend on their reputation. In order to avoid the users whose reputation values are close to give wrong appreciations, the second part of this mechanism is called “The policy of valid appreciation feedback”. This part prevents many wrong appreciations. The last part is called “Reputation management,” it can quantify the users’ behavior and provide the reference for first part and second part.
We can discover that our reputation mechanism can differentiate those people who provide good or bad resources and provide truthful or wrong appreciation. That means our mechanism can differentiate any types of users according to their behavior. Besides, we propose three measures for level dividing. The experience shows the “lower bound” efficiency is the best. Finally, we compare with other resources accessing policies. It results that our efficiency is better than them.
摘要 I
Abstract III
謝誌 V
目錄 VI
圖表索引 VIII
1. 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究流程 3
2. 文獻探討 6
2.1 架構簡介 6
2.1.1 集中式架構 6
2.1.2 非結構化全分散式架構 7
2.1.3 非結構化部份分散式架構 8
2.1.4 結構化全分散式 9
2.1.5 四種架構優缺點整理 10
2.2 名聲簡介 12
2.3 激勵理論 14
2.4 名聲機制探討 18
2.4.1 Malicious Detector Algorithm(MDA) 18
2.4.2 DCRC&CORC 19
2.4.3 小結 21
3. 研究方法 23
3.1 問題定義分析 23
3.2 研究架構 24
3.3 研究設計 26
3.3.1 運作流程 26
3.3.2 名聲計算機制 27
3.3.2.1 參數定義 27
3.3.2.2 名聲值計算方式 29
3.3.3動態存取資源機制 29
3.3.3.1層級劃分演算法 30
3.3.3.2資源存取策略 33
3.3.3.3評價有效策略 35
4. 模擬實驗設計 37
4.1 模擬實驗環境 38
4.2 模擬相關參數設定 39
4.3 實驗流程說明 39
4.4 程式運作相關模組 41
4.5 結果分析 44
5. 結論與研究限制 51
5.1 結論 51
5.2 研究限制 52
參考文獻 53
附錄A 差值分佈圖 55
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