臺灣博碩士論文加值系統

隨著資訊技術的不斷進步，各種資訊的應用也隨之不斷出現，企業利用新的技術來增進其管理效率。但是對於伺服器的管理及監控卻沒有投注相對的注意力，以致關於這方面的研究付之闕如，導致對伺服器管理的技術停滯不前。資訊系統的成功要素有許多，其中包括了系統穩定度、使用人員接受度等，而彼此之間又互成因果關係，所以有效的提高伺服器的運作穩定性如此才能讓使用人員接受度相對提高。
企業利用資訊系統對其組織、生產流程、商品和銷售進行管理的工作。網路的出現甚至改變了傳統的商業模式，讓銷售這項工作變得不再受地點、時間的限制，一般消費者或是企業員工已漸漸地習慣於使用這些資訊工具所帶來的便利，但是應用的突飛猛進也帶來了伺服器工作負擔加大的問題，這如同雙面刃一般是不可避免，而伺服器的運作是否正常直接關係到資訊系統的推廣與應用。但是目前的伺服器監控系統大多是硬體廠商所開發的，其對象是針對該公司所出品的機器為範圍，而其監控的內容大部分為硬體的損壞或異常，因此伺服器監控功能大大受限，無法監控系統內部的負載或錯誤，使得企業對於維持伺服器的穩定性依然處於被動的階段，一定是伺服器停止動作後，才可能被伺服器管理者或是使用者發現，直到伺服器管理者解決錯誤後，伺服器才恢復動作。目前有一些即時監控系統，可以代替專人看管伺服器，但是這些即時監控系統也是監控到伺服器停止動作後，才通知伺服器管理者處理，依然無法預知錯誤的發生。
對於金融、製造及電子商業伺服器必須具有高穩定性，本論文針對這樣的需求，開發出一套『以知識庫為基礎之智慧型伺服器自動監控系統』(Knowledge-based Intelligent Server-Monitoring System，簡稱KISMS)，此系統可以擷取並整合多專家的管理知識產生管理的規則並且能夠預判錯誤發生、即時監控伺服器狀態、自動處理事件和即時通知網站管理者的系統。伺服器管理者可以利用資料探勘的技術對分析伺服器監控的歷史資料進行分析找出問題，調校伺服器的穩定性，讓安裝於其上的資訊系統運作順利。
本論文的宗旨，致力於提供一個穩定性高、運作順暢的伺服器並縮短伺服器管理人員的學習曲線，讓伺服器管理者可以輕鬆的管理伺服器並保存管理知識與經驗，維持組織資訊運作正常。

Along with the continuous progress of information technology, many new types of applications of information technologies have emerged; companies use these new technologies to enhance their management efficiency. People put relatively very few focus on the management and monitoring of server, therefore, few literature can be found in this aspect and server management technology stagnating instead of forwarding. There are many factors affecting the success of an information system, among them are system stability, user acceptability, etc., these factors correlate to each other, therefore, to enhance server operation stability effectively can in turn enhance user acceptability.
Enterprise uses information system to manage its organization, process flow, merchandise and sales. The emergence of internet has changed traditional business model, it makes sales job no longer be limited by place and time, general consumer or enterprise employee are now used to the convenience brought by these information tools , but the expansions of new applications could bring more work load to the server , this is an inevitable trend , therefore , whether the server is under normal operation has a direct impact to the widespread use and application of information system . Unfortunately, the monitoring system available currently in the market are developed by hardware vendors, it aims at solving the trouble from machines produced by them, in the mean time, the major monitoring content is the damage or abnormity of hardware. Therefore, the server monitoring function is still limited, it can not monitor the loading or mistake inside the system, enterprise still stays at a passive stage to maintain the stability of the server, problem can only be found by the server manager or server user after the server has stopped functioning, and the server goes back to function properly only when the problems are solved by server manager. Currently, some real time monitoring system can replace a dedicated person’s job to watch the server, but the disadvantage of this system is that these real time monitoring systems only notify the server manager when they detect the shutdown of the server; they still lack the ability of preventing errors from happening.
Servers used in financial, manufacturing or e-commerce need to be very highly stable, this study aims at developing “Knowledge-based Intelligent Server-Monitoring System” to fit the stability requirements, this system can acquire and integrate multiple experts management knowledge, it can also generate management rule and predict the happening of errors, it monitors the server status in real time, it is a system that can handle an event automatically and notify webmaster in real time. Server manager can use data exploring technique to analyze the server monitoring historical data in order to find out the problems, server manager can also adjust the server stability and let the information system installed in it run smoothly.
The main purposes of this study is to provide a highly stable, smooth running server and shorten the learning curve of server managers, therefore, server managers could manage server in much easier way and management knowledge and experiences can be preserved, in the mean time, normal organization information operation can be maintained.

中文摘要 I
ABSTRACT III
致謝 V
目錄 VI
表目錄 X
圖目錄 XI
圖目錄 XI
第一章、緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 4
第二章、研究背景與相關技術 5
2.1 主機管理模式 5
2.1.1 主機代管( Co - location ) 5
2.1.2 專人管理（自設機房、管理員） 7
2.1.3 即時監控系統（主機狀態自我偵測） 8
2.1.4 電子商務環境即時監控系統(EDCS) 11
2.2 知識擷取的方法 12
2.2.1 凱利表格（Repertory Grid） 12
2.2.2 隱含知識的擷取技術 EMCUD（Embedded Meaning under Uncertainty Deciding） 16
2.3 知識整合的技術 18
2.3.1 多專家知識表格擷取（Multiple-Expert Repertory Grid Elicitation，MERGE） 19
2.3.2 模糊知識表格（Fuzzy table） 19
2.3.3 基因演算法知識整合架構（GA-Based knowledge-integration framework） 20
2.3.3.1 編碼及解碼方式，為解決問題之字串表示方法 22
2.3.3.2 建立初始群組，即產生起始解及決定群體數目大小 23
2.3.3.3 適應度函數（Fitness Function） 24
2.3.3.4 選擇運算子 24
2.3.3.5 基因運算子 25
2.3.3.6 控制參數的設定 26
2.4 模糊變量成對比較矩陣（FUZZY Pair-Wise Comparison matrix） 27
2.4.1 分析層級程序法（traditional Analytic Hierarchy Process，AHP） 27
2.4.2 模糊變量成對比較矩陣（Pair-Wise Comparison Matrix with fuzzy items） 30
第三章、多專家管理知識的擷取及整合方法 33
3.1 定義管理知識的目標及範圍 34
3.2 建立概念表格 35
3.3 建立共同概念表格 36
3.4 計算專家權重 39
3.5 評等概念表格並計算概念權重 41
3.5.1 決定評等目標採用模糊量 41
3.5.2 利用模糊變量評等概念 42
3.5.3 計算概念的幾何平均數及權數 42
3.6 評等目標/概念表格（Concept-Object Grid） 44
3.6.1 訂定模糊語意值（Fuzzy Value） 45
3.6.2 進行目標/概念表格評等 45
3.7 整合模糊知識及產生規則 47
3.8 結語 49
第四章、以知識庫為基礎之智慧型伺服器動監控系統(Knowledge-based Intelligent Server-Monitoring System) 50
4.1 KISMS 系統概述 50
4.2 KISMS 系統架構 51
4.2.1知識擷取暨整合子系統 53
4.2.2伺服器即時監控子系統 54
4.3 KISMS 系統處理流程 56
4.3.1專家知識及擷取流程 56
4.3.2 伺服器狀態監控流程 58
4.3.3 人員通知暨歷史資料查詢流程 59
4.4 KISMS 技術應用 60
4.4.1 WMI 應用 60
4.4.2 傳送及接收電子信件應用 63
4.4.3知識庫(Knowledge-Based)之建制 64
4.4.3 SQL Server 2000的簡介 65
4.5 結語 67
第五章、KISMS的系統實做 68
5.1系統設定操作介面(KISMS Manager) 68
5.2 知識擷取暨整合模組（Knowledge Elicitation and Integration module） 72
5.3 偵測程式(Detective Module) 79
5.4 查詢紀錄模組 86
5.5 結語 87
第六章、KISMS的實驗與評估 88
6.1 實驗環境 88
6.2 實驗架構 89
6.3 實驗結果 91
第七章、結論與未來發展 94
參考文獻 96

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