Extended Method of Evidence Theory for Pervasive Computing

As a new kind of computing paradigm, pervasive computing changes the idea of what is computing radically. Because it fuses relative multi-source information among different computing nodes, a kind of paradigm with fusion computing can be regarded, which supply information access computing service for people by information fusion from multiple levels and multiple visions confidently, credibly and conveniently. Owing to the need of pervasive computing, extended method of evidence theory is studied, which can assess reliability of multi-source evidence context-aware by credibility factor, add mass belief function by time-difference-calibration and power function by correlative degree among evidences to classic D-S method of evidence theory under considering the associated relationships between validity and time-efficiency independency of evidences. The mass belief function has timely tracked dynamic process of evidences. The power function has measured correlative degree of evidences, based on this correlative degrees, de-correlation work can be done by transforming for conflict evidences. The method extends and improves the classic D-S method, overcomes its shortcoming, updates and improves QoS of different application fields, ensures and implements the target of pervasive computing paradigm. By application examples of Smart Space, such as Smart Meeting Room, as a test bed of pervasive computing paradigm, the validity of its extension and improvement has been tested successfully.