›› 2010, Vol. 25 ›› Issue (3): 499-508.

Special Issue: Computer Architecture and Systems

• Special Section on Trends Changing Data Management • Previous Articles     Next Articles

A Solution of Data Inconsistencies in Data Integration --- Designed for Pervasive Computing Environment

Xin Wang (王欣), Student Member, CCF, Lin-Peng Huang (黄林鹏), Senior Member, CCF, Yi Zhang (章义), Xiao-Hui Xu (徐小辉), Student Member, CCF, and Jun-Qing Chen (陈俊清), Student Member, CCF   

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2009-06-29 Revised:2010-02-22 Online:2010-05-05 Published:2010-05-05
  • About author:
    Xin Wang received the B.S. and M.S. degrees in computer science from Shandong University. She is currently a Ph.D. candidate in the Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China. She is a student member of China Computer Federation. Her research interests include data integration and data uncertainty.
    Lin-Peng Huang is a professor of Department of Computer Science & Engineering, Shanghai Jiao Tong University and a senior member of China Computer Federation. His general interests include distributed computing, service computing and program language.
    Yi Zhang received the B.S. and M.S. degrees in computer science from Shandong University. He is currently a Ph.D. candidate in the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China. His research interests include data integration and distributed computing.
    Xiao-Hui Xu received the B.S. and M.S. degrees in computer science from Chongqing University. He is currently a Ph.D. candidate in the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China. He is a student member of China Computer Federation. His research interests include service computing and software reliability.
    Jun-Qing Chen received his B.S. and M.S. degrees in computer science from Fuzhou University. He is currently a Ph.D. candidate in the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China. He is a student member of China Computer Federation. His current research interests include type and effect system, formal analysis and verification service composition and dynamic service update in OSGi.
  • Supported by:

    This work was supported by the National Natural Science Foundation of China under Grant No. 60970010; the National Basic Research 973 Program of China under Grant No. 2009CB320705; and the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20090073110026.

New challenges including how to share information on heterogeneous devices appear in data-intensive pervasive computing environments. Data integration is a practical approach to these applications. Dealing with inconsistencies is one of the important problems in data integration. In this paper we motivate the problem of data inconsistency solution for data integration in pervasive environments. We define data quality criteria and expense quality criteria for data sources to solve data inconsistency. In our solution, firstly, data sources needing high expense to obtain data from them are discarded by using expense quality criteria and utility function. Since it is difficult to obtain the actual quality of data sources in pervasive computing environment, we introduce fuzzy multi-attribute group decision making approach to selecting the appropriate data sources. The experimental results show that our solution has ideal effectiveness.


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