Context is any information that can enhance a computing system’s relevance, timeliness, and usefulness to the user. Recent research has been devoted to the use of context in a mobile environment, particularly in handling the mobility itself. This chapter will start with defining what context is, how it is represented, and present a generalized system architecture. The authors then look at the problem of mobility in general and discuss existing solutions. Next they show how context can be leveraged to achieve more intelligent mobility management decisions. The authors highlight some of the research issues particular to context-aware mobility management and survey existing solutions. Last, they argue that these solutions have not truly addressed these issues and present their own architecture for handling mobility.
In this section we attempt to define what context is and discuss some ways of modelling it. We also discuss the generalized framework for context-aware systems.
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:
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.
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 This imperfection stems from a number of reasons, such as sensors becoming faulty or information getting quickly out of date.
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.
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.
Key Terms in this Chapter
Mobility Management: Management of the communications aspect as an entity (user or device) moves from one location to another so that network Quality of Service is maintained.
Handoff (also known as handover): The process wherein a device transfers from one network point of attachment to another.
Ontology: A formal definition of a common set of terms that are used to describe and represent a domain.
Horizontal Handover: Handover on the same type of mobile network interface.
Protocol: Special set of rules that end points in a telecommunications network use when they communicate.
Context: Any information that can be used to characterize the situation of an entity. Typical examples are location, identity, and state of people and computational objects.
Context Aware System: Computing system that provides relevant services and information to users based on their situational conditions.