Authors: De-gan Zhang
Addresses: Tianjin Key Lab of Intelligent Computing and Novel Software Technology, Tianjin University of Technology, Tianjin, 300191, China; Key Laboratory of Computer Vision and System, Tianjin University of Technology, Ministry of Education, Tianjin, 300191, China; Key Lab of Industrial Controlling Technology, Zhejiang University, Hangzhou, 310027, China
Abstract: It is known to all that context-aware computing with uncertainty is an important part of pervasive computing for proactive service. Because multi-source evidence context-aware information with uncertainty is dynamic and changing randomly, in order to ensure the QoS of different application fields based on pervasive computing, we modified the fusion method of evidence information after considering context|s reliability, time efficiency and relativity, which has improved the classic fusion rule of D-S evidence theory when used in the pervasive computing paradigm. After extending the process, we overcome the shortcoming of classic D-S evidence theory. All these suggested technologies have been successfully used in our project. The efficiency of our researches has been tested by application practice and validation of the demo.
Keywords: proactive services; context-aware computing; D-S evidence theory; uncertainty; fusion; context awareness; pervasive computing; quality of service; QoS.
International Journal of Modelling, Identification and Control, 2009 Vol.8 No.3, pp.248 - 255
Available online: 17 Nov 2009Full-text access for editors Access for subscribers Purchase this article Comment on this article