Context Aware Mobility Management

What is Context?

The term context has been defined in many ways and in many forms, but up to the time of this writing no single definition of context has been put forth that sufficiently captures all the various aspects of this term. Perhaps this reflects the existing “paradox” in context-aware computing. Understanding the concept of context is in itself one of the fundamental research challenges in this field (Schmidt, 2002).

The most widely accepted definition is by Dey (2001), defining context as “any information that can be used to characterize the situation of an entity” (p. 5). This very general definition of context by Dey has been formally extended by Zimmerman, et al (2007) to include a description of context using five fundamental categories, namely individuality, activity, location, time, and relations. In an attempt to better understand context, Henricksen, et al (2002) described it using the following characteristics:

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  Context information can be static or dynamic. This implies that context exhibit temporal characteristics, as frequently we are not just interested of present context values but past and future (predicted) context as well.

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  Context is imperfect – it can present contradicting, incomplete or even incorrect information. This imperfection stems from a number of reasons, such as sensors becoming faulty or information getting quickly out of date.

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  Context can be represented in many ways. A significant gap exists between data captured from sensor outputs and the level of context needed by applications. A context model must be flexible enough to handle the different levels of granularity demanded by various applications.

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  Relationships exist between context information. This relationship can be as simple as ownership, and can be exploited to infer that presence of a device mean presence of a person. A person’s location also pinpoints his activity, if he is at a gym he is most probably engaging in some sort of exercise.