Cloud Intelligent Services for Calculating Emissions and Costs of Air Pollutants and Greenhouse Gases

  • Thanh Binh Nguyen
  • Fabian Wagner
  • Wolfgang Schoepp
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6591)

Abstract

The GAINS (Greenhouse gas – Air pollution Interactions and Synergies) model quantifies the full DPSIR (demand-pressure-state-impact-response) chain for the emissions of air pollutants and greenhouse gases. To fulfill regional specific requirements of the GAINS model, we have studied and developed a cloud intelligent service system for calculating emissions and costs for reducing emissions at regional as well as global levels. In this paper, first we present a cloud intelligent conceptual model that is used to specify an application framework, namely GAINS cloud intelligent application framework. Using this application framework, first we build a global data warehouse called GAINS DWH World, then a class of regional data warehouses, e.g. GAINS DWH Europe, GAINS DWH Asia, etc, are specified and used for regional data analysis and cost optimization.

Keywords

GAINS Cloud intelligence Data Warehouse 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Binh, N.T., Wagner, F., Schoepp, W.: GAINS-BI: Business Intelligent Approach for Greenhouse Gas and Air Pollution Interactions and Synergies Information System. In: Proc of the International Organization for Information Integration and Web-based Application and Services, IIWAS 2008, Linz (2008)Google Scholar
  2. 2.
    Gangadharan, G.R., Swami, S.N.: Business Intelligence Systems: Design and Implementation Strategies. In: Proc. of the 26th International Conference Information Technology Interfaces, ITI 2004, Croatia, pp. 139–144 (2004)Google Scholar
  3. 3.
    Grant, A.J., Luqi: Intranet Portal Model and Metrics: A Strategic Management Perspective. IT Professional 7, 37–44 (2005)CrossRefGoogle Scholar
  4. 4.
    Hugh, J.W., Barbara, H.W.: The Current State of Business Intelligence. Computer 40, 96–99 (2007)Google Scholar
  5. 5.
    Klaassen, G., Amann, M., Berglund, C., Cofala, J., Höglund-Isaksson, L., Heyes, C., Mechler, R., Tohka, A., Schöpp, W., Winiwarter, W.: The Extension of the RAINS Model to Greenhouse Gases. An interim report describing the state of work as of April 2004 (2004), IIASA IR-04-015 Google Scholar
  6. 6.
    Lou, A.: Data Warehousing in the Clouds Making Sense of the Cloud Computing Market (2009), White paper http://www.b-eye-network.com/view/8702
  7. 7.
    Makowski, M.P.: Data Cleaning and Performance Tuning in the GAINS Model. Thesis at the Database and Artificial Intelligence Group (DBAI) of the Technical University of Vienna (2008)Google Scholar
  8. 8.
    Michael, A., Armando, F., Rean, G., Anthony, D., Randy, K., Andy, K., Gunho, L., David, P., Ariel, R., Ion, S., Matei, Z.: Above the Clouds: A Berkeley View of Cloud Computing, University of California at Berkeley (2009)Google Scholar
  9. 9.
    Ta’a, A., Bakar, M.S.A., Saleh, A.R.: Academic business intelligence system development using SAS® tools. In: Online Proc. of the SAS Global Forum (2008)Google Scholar
  10. 10.
    Tvrdikova, M.: Support of Decision Making by Business Intelligence Tools. In: Proc. of the 6th International Conference on Computer Information Systems and Industrial Management Applications, pp. 364–368 (2007)Google Scholar
  11. 11.
    Wei, X., Xiaofe, X., Lei, S., Quanlong, L., Hao, L.: Business intelligence based group decision support system. In: Proc of the International Conferences on Info-tech and Info-net ICII 2001, Beijing, China, pp. 295–300 (2001)Google Scholar
  12. 12.
    Zeng, L., Shi, Z., Wang, M., Wu, W.: Techniques, Process, and Enterprise Solutions of Business Intelligence. In: Proc. of the IEEE Conference on Systems, Man and Cybernetics, Taipei, Taiwan, pp. 4722–4726 (2006)Google Scholar
  13. 13.
    Wagner, F., Schoepp, W., Heyes, C.: The RAINS optimization module for the Clean Air For Europe (CAFE) Programme, Interim Report IR-06-029, International Institute for Applied Systems Analysis (IIASA) (September 2006)Google Scholar
  14. 14.
    Wang, L., Laszewski, G., Kunze, M., Tao, J.: Cloud computing: A Perspective study. Grid Computing Environments (GCE) (2008)Google Scholar
  15. 15.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Thanh Binh Nguyen
    • 1
  • Fabian Wagner
    • 1
  • Wolfgang Schoepp
    • 1
  1. 1.International Institute for Applied Systems Analysis (IIASA)LaxenburgAustria

Personalised recommendations