一种面向主动服务的情境觉察计算方法

张德干; 黄孝斌

doi:10.1360/aas-007-0860

一种面向主动服务的情境觉察计算方法

doi: 10.1360/aas-007-0860

1.
Department of Computer Science and Technology, Tianjin University of Technology, Tianjin 300191, P.R.China
2.
Key Laboratory of Industrial Controlling Technology, Zhejiang University, Hangzhou 310058, P.R.China
3.
Beijing Bestpower Electrical and Engineering Ltd., Beijing 100096, P.R.China

详细信息

通讯作者:
张德干

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- 被引次数: 0
出版历程
- 收稿日期: 2006-01-04
- 修回日期: 2006-08-22
- 刊出日期: 2007-08-20

A Kind of Context-aware Computing Approach for Proactive Service

1.
Department of Computer Science and Technology, Tianjin University of Technology, Tianjin 300191, P.R.China;
2.
Key Laboratory of Industrial Controlling Technology, Zhejiang University, Hangzhou 310058, P.R.China;
3.
Beijing Bestpower Electrical and Engineering Ltd., Beijing 100096, P.R.China

More Information

Corresponding author: ZHANG De-Gan

摘要

摘要: We focus on modeling and computing of aware context with uncertainty for making dynamic decision during seamless mobile service. We re-examine formalism of random set, which is not finite-set statistics (FISST), argue the limitations of the direct numerical approaches, give new modeling mode based on random sets theory (RST) for aware context, and propose our computing approach of modeled aware context. In addition, we extend classic D-S evidence theory after considering reliability, time efficiency, relativity of context, and compare these two kinds of relative computing methods for uncertain context. By comparing, the validity of new context-aware computing approach based on improved random set theory (IRST) or extended D-S evidence theory (EDS) for proactive service has been tested.
- Proactive service /
- context-aware /
- random set theory /
- D-S evidence theory
Abstract: We focus on modeling and computing of aware context with uncertainty for making dynamic decision during seamless mobile service. We re-examine formalism of random set, which is not finite-set statistics (FISST), argue the limitations of the direct numerical approaches, give new modeling mode based on random sets theory (RST) for aware context, and propose our computing approach of modeled aware context. In addition, we extend classic D-S evidence theory after considering reliability, time efficiency, relativity of context, and compare these two kinds of relative computing methods for uncertain context. By comparing, the validity of new context-aware computing approach based on improved random set theory (IRST) or extended D-S evidence theory (EDS) for proactive service has been tested.
- Proactive service /
- context-aware /
- random set theory /
- D-S evidence theory