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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68799

    Title: 分散式系統的個人化漸增式貢獻度模型;Personalized Incremental Credit Computation Model for Distributed System
    Authors: 鄭智陽;Zheng,Zhi-yang
    Contributors: 資訊工程學系
    Keywords: 分散式系統;聲望;信任模型;漸增法;distributed system;reputation;trust model;incremental
    Date: 2015-07-28
    Issue Date: 2015-09-23 14:29:20 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究設計了一個使用者的貢獻度評分模型並應用於 WeOS 平台。WeOS 平台是一個以 P2P ( Peer-to-Peer )的網路架構組成的網頁應用平台,使用者可以在 WeOS 平台上發布自己開發的應用程式(網頁),以及使用其他人所開發的應用程式(網頁)。WeOS 上採用了 AID (Autonomous Identity )的機制,讓使用者自主管理自己的帳號。帳號的註冊資訊僅存在於使用者本機的電腦上,並不會存在中央伺服器。在沒有中央伺服器的環境下,如何有效的管理使用者在社群網路上的活動、辨識使用者信賴與否,成了一個重要的議題。
    本研究設計了一個可以分散式進行的量化方式,根據使用者在網路中的行為和評價來決定使用者在網路中的貢獻度。根據此貢獻度,使用者們可以挑選較值得信賴的資訊來源與服務提供者。貢獻度機制是 WeOS 的核心之一,在未來,在各個服務之間的交流將會以使用者的貢獻度作為參考依據。
    然而個人化的衡量方式,將會產生大量的計算和資料量,對單一伺服器將會造成龐大的負擔,並且難以達成即時更新。我們利用了 WeOS 平台上 P2P 的特性,將工作分散至多個節點進行計算、資料分散儲存,進而減少單一節點的負擔,並且加速了更新的速度,讓貢獻度數值能夠更準確、更快速的呈現於使用者。
    ;This paper is designed and applied for the WeOS platform. The WeOS platform is a web app platform based on P2P (Peer-to-Peer) structure network. Users can use the application which is developed by others and they can upload their application as well. The WeOS takes the AID (Autonomous Identity) mechanism and that makes users can manage their identities autonomously. Users can manage their identities and data on the client side with the support of AID. The users’ identities will not store in a central server. In such environment, how can we supervise users’ activity and identify a trusty user without a central server is a hard issue.
    We design a metric to evaluate a user’s credit according the user’s actions and reputations on the net. Users can select the trusty information source and service provider with the help of credit. The credit will be one of the most important modules in the WeOS. In the future, users’ reactions between service and service should refer to their credit.
    We think that comment is a subjective action. Everyone can have their own view and it will be very different each other. The traditional reputation models are usually global. Users are not always persuaded by the global value, so we adopt the personal mechanism. We try to make the credit value can express users’ self-experience.
    However, the personal mechanism will make the computation and storage requirement increase heavily. It is a big loading for a central server to handle that and it is hard to update the value immediately. We take advantage of P2P’s feature of the WeOS platform to separate the task to several nodes. That will share the loads on server and make the procedure can complete rapidly. With the shorter updating cycle, the credit will reveal the users’ behavior more correctly.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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