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研究生:蔡秉諺
研究生(外文):Ping-YenTsai
論文名稱:應用AHP於綠色資料中心改善優先順序決策模式
論文名稱(外文):A Study of AHP on Prioritizing Improvement Activities for Green Data Center
指導教授:王泰裕王泰裕引用關係
指導教授(外文):Tai-Yue Wang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工業與資訊管理學系專班
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:83
中文關鍵詞:節能綠色資料中心層級分析法
外文關鍵詞:Energy SavingGreen Data CenterAnalytic Hierarchy Process Theory
相關次數:
  • 被引用被引用:8
  • 點閱點閱:427
  • 評分評分:
  • 下載下載:114
  • 收藏至我的研究室書目清單書目收藏:0
近年來,隨著環保意識抬頭,企業開始注意到資料中心能源消耗的問題,用電成本更是資料中心總成本中不斷增加的一部分。傳統的資料中心,要節省電能的消耗是很困難的,必須重新檢討並藉由綠色科技(Green IT)來做最佳改善,將現有的資料中心轉換成高效能的綠色資料中心(Green Data Center)。在轉換的過程中,需考慮的因素及其重要性,成為本研究之動機。
然而,企業在有限的時間、人力及預算下,大多無法一次完成所有的改善工作,因此,本研究嘗試建立了一個公正且客觀的決策模式。在第一階段的工作主要是先透過文獻探討,彙整出影響綠色資料中心的構面及要素,並對6位專家進行深度訪談,確認資料中心能源效率改善之衡量指標及評估準則,並依此建立層級架構。第二階段再運用AHP專家問卷,對15位專家進行問卷調查,並使用Super Decisions軟體計算各項權重與一致性檢定。
分析結果顯示,整體專家認為評估構面改善優先順序為:「冷卻系統」(0.3466)、「減少資源浪費」(0.2666)、「電源管理」(0.2084)、「儲存設備」(0.1784)。
Recently, with the rise of the sense of environment protection, enterprises get aware of the problem of energy consumption in the data centers while the cost of electricity for data centers also keeps increasing. It is fairly difficult to reduce the energy consumption for traditional data center; instead, Green IT should be considered for the best solution to turn the existing data center into Green Data Center with high efficiency. In the process of this transformation, the factors and importance that should be taken into account become the research motive for the present study.
However, with the limited time, human resource, and budget, enterprises are not able to accomplish all the jobs at a time. Therefore, the present study attempts to establish an impartial and objective model for decision making. In phase 1, the key elements and scopes for Green Data Center are summarized and categorized through bibliography investigation. In addition, profound interviews with 6 experts are conducted to confirm the standards and criteria for measuring and evaluating the energy efficiency of data centers and to build up the hierarchy structures. In phase 2, AHP questionnaire is performed by 15 experts and Super Decision software is applied to calculate the weight of each factor and test the consistence.
The analysis result shows that the priority of improvement for all the evaluated factors is cooling system (0.3466), reduction of resource wasting (0.2666), power management (0.2084), and storage device (0.1784).
摘要..............................................I
Abstract .........................................II
誌謝..............................................III
目錄..............................................IV
表目錄.............................................VI
圖目錄.............................................VII
第一章 緒論.........................................1
1.1 研究背景與動機 ..................................1
1.2 研究目的........................................2
1.3 研究對象........................................3
1.4 研究範圍與研究假設...............................3
1.5 研究流程........................................4
1.6 論文架構........................................6
第二章 文獻探討......................................7
2.1 資料中心能源效率指標..............................7
2.2 資料中心能源使用狀況..............................8
2.3 影響綠色資料中心的構面及要素.......................11
2.4 多準則決策.......................................19
2.5 應用AHP於優先順序之相關研究........................27
2.6 小結 ............................................30
第三章 研究設計與方法..................................31
3.1評估指標及準則選取原則..............................31
3.2評估架構建立.......................................32
3.3評估架構確認.......................................40
3.4權重之求取.........................................41
第四章 資料分析與研究結果...............................43
4.1 專家訪談..........................................43
4.2 問卷設計與統計分析.................................48
4.3 小結..............................................57
第五章 結論與建議.......................................58
5.1 結論..............................................58
5.2 建議..............................................59
參考文獻...............................................60
附錄一.................................................67
附錄二.................................................77
中文部分
余如容(2012),「應用層級分析法探討推動太陽能政策之優先順序」,碩士論文,朝陽科技大學環境工程與管理系。
財團法人台灣綠色生產力基金會(2010),2010年非生產性質行業能源查核年報。
財團法人台灣綠色生產力基金會(2010),電信網路機房節能應用手冊。
張國榮(2005),「應用AHP評定河川環境營造工程興建優先順序」,碩士論文,中興大學土木工程研究所。
蔡岳儒(2009),「以層級分析法評估國民小學推動永續校園之優先順序」,碩士論文,朝陽科技大學環境工程與管理系。
林世弘(2009),「應用多評準決策於集水區治理優先順序評估-以台北市信義區為例」,碩士論文,逢甲大學水利工程與資源保育研究所。
鄧振源、曾國雄(1989),層級分析法(AHP)的內涵特性與應用(上),中國統計學報,第27卷,第6期。
鄧振源、曾國雄(1989),層級分析法(AHP)的內涵特性與應用(下),中國統計學報,第27卷,第7期。
鄧振源(2005),計畫評估-方法與應用(第二版),華梵大學運籌規劃與管理研究中心。
謝文憲(2005),「農業灌溉渠道更新改善優先順序決策模式之研究-以嘉南農田水利會新營區管理處轄內支線為例」,碩士論文,國立成功大學土木工程研究所。
簡楨富(2005),決策分析與管理,雙葉畫廊有限公司,台北。

英文部分
Belady, C., Rawson, A., Pflueger, J., and Cader, T. (2008). Green Grid Data Center Power Efficiency Metrics:PUE and DCIE. The Green Grid, White Paper #6.
Corrigan, M. K. (2009). Strategies for a Sustainable Green Enterprise. The Green FederalEnterprise, Sigma, 5-9.
Cho, J. and Kim, B. S. (2011). Evaluation of air management system’s thermal performance for superior cooling efficiency in high-density data centers. Energy and Buildings , 43, 2145–2155.
Dukes, S. (1984). Phenomenological methodology in the human sciences. Journal of Religion and Health, 23(3), 197-203.
EPA (2007). Report to Congress on Server and Data Center Energy Efficiency Public Law 109-431. U.S. Environmental Protection Agency ENERGY STAR Program.
Fakhim, B., Behnia, M., Armfield, S. W., and Srinarayana, N. (2011). Cooling solutions in an operational data centre: A case study. Applied Thermal Engineering, 31, 2279-2291.
Garbin, D. A. and Chang, E. W. (2009). Green Data Center Management, The Green Federal Enterprise, Sigma.
Gowri, K. (2005). Desktop Tools for Sustainable Design. American Society of Heating, Refrigerating and Air-Conditioning Engineers.
Greenberg, S., Tschudi, W., and Weale, J. (2006). Self Benchmarking Guide for Data Center Energy Performance (Version 1.0). Technical report, Lawrence Berkeley National Laboratory (LBNL).
Greenberg, S., Khanna, A., and Tschudi, W. (2009). High Performance Computing with High Efficiency. ASHRAE Transactions TRNS-00232-2008. In press. To be presented at the ASHRAE Annual Conference, Louisville KY.
Harmon, R. R. and Auseklis, N. (2009). Sustainable IT Services: Assessing the Impact of Green Computing Practices. PICMET 2009 Proceedings, PICMET/IEEE.
Kant, K. (2009). Data Center Evolution: A Tutorial on State of the Art, Issues, and Challenges. Journal of Computer Networks, 53, 2939–2965.
Liu, J., Zhao, F., Liu, X., and He, W. (2009). Challenges Towards Elastic Power Management in Internet Data Centers. 2009 29th IEEE International Conference on Distributed Computing Systems Workshops, 65-72.
Langer, S. G. and French, T. (2011). Virtual Machine Performance Benchmarking. Journal of Digital Imaging, 24, 883-889.
Masanet, E. R., Brown, R. E., Shehabi, A., Koomey, J. G., and Nordman, B. (2011). Estimating the Energy Use and Efficiency Potential of U.S. Data Centers. Proceedings of the IEEE, 99(8), 1440-1453.
Mata-Toledo, R. and Gupta, P. (2010). Green Data Center: How Green can we perform?. ASBBS Annual Conference, Las Vegas, 566-571.
Pflueger, J. (2008). Re-defining the ‘green’ data center. Dell Technical White paper.
Schmidt, R. and Iyengar, M. (2005). Effect of Data Center Layout on Rack Inlet Air Temperatures. The Pacific Rim/ASME International Electronics Packaging Technical Conference and Exhibition.
Sharavanan, S., Poongodi, D., and Kumar, A. R. (2010). Towards Green Computing: Energy Efficient Data Centers. Journal of Mathematics and Technology, 131-135.
Sharma, R. K., Bash, C. E., and Patel, C. D. (2002). Dimensionless Parameters for the Evaluation of Thermal Design and Performance of Large-Scale Data Centers. AIAA, AIAAe3091.
Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
Sun, H. S. and Lee, S. E. (2006). Case Study of Data Centers’ Energy Performance. Energy and Buildings, 38, 522–533.
Silva, L. M., Alonso, J., and Torres, J. (2009). Using Virtualization to Improve Software Rejuvenation. IEEE Transactions on Computers, 58(11), 1525-1538.
Torres, J., Carrera, D., Hogan, K., Gavalda, R., Beltran, V., and Poggi, N. (2008). Reducing Wasted Resources to Help Achieve Green Data Centers. IEEE International Symposium on Parallel and Distributed Processing, 1-8.
Ye, K., Huang, D., Jiang, X., Chen, H., and Wu, S. (2011). Virtual Machine Based Energy-Efficient Data Center Architecture for Cloud Computing: A Performance Perspective. IEEE/ACM International Conference on Green Computing and Communications (GreenCom) & International Conference on Cyber, Physical and Social Computing (CPSCom) .
Yoon, K. P. and Hwang, C. L. (1995). Multiple Attribute Decision Making: An Introduction. Sage Publications, Newbury Park, CA.
Zhang, X., Zhao, X. N., and Zeng, L. J. (2010). Key Technologies for Green Data Center. IEEE Third International Symposium on Information Processing, 477-480.

網站部分
Google. (2011). Data Center Efficiency Measurements. Retrieved November 8, 2011, from Google: http://www.google.com/corporate/datacenters/measuring.html

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