An adaptive modelling infrastructure for context-aware mobile computing

Cheung, Ronnie Chu-Ting (2011) An adaptive modelling infrastructure for context-aware mobile computing. Doctoral thesis, London Metropolitan University.

[img]
Preview
Text
549553.pdf - Published Version

Download (3MB) | Preview

Abstract / Description

Context provides information about the present status of people, places, things, network and devices in the environment. Context-awareness refers to the use of context information for an application to adapt its functionality to the current context of use. Development of context-aware applications is inherently complex. Previous researches on mobile computing emphasize on programmable interfaces for development of context-aware systems. There are limited researches that emphasize on the modelling aspects of adaptive applications. This research aims at developing a complete infrastructure for development of context-aware applications. The infrastructure consists of a middleware for context-aware application development that is supported by a set of context information modelling and reasoning facilities. It aims at extending the capabilities of context-aware middleware infrastructures by incorporating novel approaches to model context and situations under uncertainty. This thesis addresses the key challenges in context-aware computing by a complete infrastructure that aims at achieving the following: (1) support for fuzzy composition of high level context abstraction from low level detector context, and fuzzy-based inference mechanisms, (2) support for mobile services that can be dynamically composed and migrated with reference to adaptation requirements for different context situations, (3) support for modelling of adaptation components and entities.

Item Type: Thesis (Doctoral)
Additional Information: uk.bl.ethos.549553
Uncontrolled Keywords: adaptive applications; context-awareness; context-aware systems; computing; mobile computing; middleware
Subjects: 000 Computer science, information & general works
Department: School of Computing and Digital Media
Depositing User: Chiara Repetto
Date Deposited: 03 May 2022 09:48
Last Modified: 03 May 2022 09:48
URI: http://repository.londonmet.ac.uk/id/eprint/7545

Downloads

Downloads per month over past year



Downloads each year

Actions (login required)

View Item View Item