A QoC Based Method for Reliable Fusion of Uncertain Pervasive Contexts

With the rapid development of information technology, it is inevitable that the distributed mobile computing will evolve to pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in. However, most of WSN contexts coming from may be more and more unstructured, widespread and massive. Therefore, to realize precise location, adaptive reasoning and reliable fusion of these kinds of contexts, we should sense the changes of them efficiently and accurately in real time. One of the problems is how to assure the reliability of context fusion in the complex situations context fluctuating frequently. Many attentions have been paid to the research of the context-aware pervasive applications. However, most of them just use the raw context directly or take just some aspects of the Quality of Context (QoC) into account. Therefore, we propose an uncertain context fusion framework that supports QoC management in various layers. By this framework, we can use threshold management, quality factor management and inconsistent context management to protect and provide QoS-enriched context fusion efficiently for context-aware applications and services such as complex Internet of Vehicles.