Pervasive computing: concepts, technologies and applications by Guo, Minyi; Shen, Yao; Tang, Feilong; Zhou, Jingyu

By Guo, Minyi; Shen, Yao; Tang, Feilong; Zhou, Jingyu

This publication introduces primary ideas and theories in pervasive computing in addition to its key applied sciences and purposes. It explains tips on how to layout and enforce pervasive middleware and genuine software platforms, masking approximately all points regarding pervasive computing. Key applied sciences within the ebook contain pervasive computing-oriented source administration and activity migration, cellular pervasive transaction, human machine interface, and context collection-oriented instant sensor networks.

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Extra resources for Pervasive computing: concepts, technologies and applications

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From the collection point of view, context can be categorized as direct context and indirect context. Direct context refers to gathered information that does not involve any extra processing. If the information is gathered implicitly by means of sensors, it is called sensed context. If the information is gathered explicitly, it is called defined context. Indirect context refers to one inferring information from direct context. From the application point of view, context falls into low-level context and highlevel context.

2 In this step, evidence is propagated to all the sensors and objects. With the help of the mapping function, the masses of sensors are transferred to the objects layer. 4 Propagating Evidence in the Objects Layer After the masses of sensors are transferred, this step further propagates the evidence in the objects layer. 1. 9 confidence about object o5 when we observe object o1. We take simple object o4, deduced object o5, and composite object o6 to explain this step. ◾ Calculating masses for the deduced objects: DO ← E.

What is more, context may be fuzzy. Some context is imprecise and incomplete. It is a known fact that sensors are not 100% accurate. Besides, multiple sensors might provide different values for the same context. Classifying context is important for managing context quality as well as understanding the context and application development. 1 Different levels of context. various context based on their characteristics, according to different classification principles. From the collection point of view, context can be categorized as direct context and indirect context.

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