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Resource availability awareness and data utility: The foundation for a DSS framework in a pervasive computing environment

Posted on:2009-03-19Degree:Ph.DType:Dissertation
University:University of Maryland, Baltimore CountyCandidate:Russell, StephenFull Text:PDF
GTID:1448390002991832Subject:Information Science
Abstract/Summary:
The reality of pervasive computing has nearly been realized, if it has not already. Pervasive computing environments promise ubiquitous connectivity, a plethora of information, and seamless computing support. Despite the advances in infrastructure to deliver on Weiser's original vision for pervasive computing environments, little attention has been specifically given to decision support systems that are expected to operate in these environments. Issues such as large amounts of highly variant data and decision resource availability can directly influence decision support systems and subsequently limit the efficacy of the support they provide. Moreover, these factors can have a direct effect on decision outcomes for deterministic structured and semi-structured problems. This research investigates the impact of data utility enhancement and availability awareness on decision making and decision support systems. A decision support system architecture that addresses the limitations caused by the large amounts of variant data and uneven conditioning of connectivity that are characteristic in pervasive computing environments is proposed and developed. By incorporating data utility enhancement, availability awareness, and an agent-based framework, the decision support system architecture seeks to extend the breadth of decision support systems research. This architecture, which we call the Pervasive Agent Decision Support System (PADSS), integrates intelligent agents, wavelets, and instant messaging as a comprehensive decision support solution to address data utility and resource availability related issues in pervasive computing environments. As such, this research study combines several experiments that include qualitative evaluation, empirical evaluation, mathematical modeling, and simulation in a design science context. The culmination of the research concludes with an implementation and evaluation of a pervasive computing DSS based on the presented DSS architecture.
Keywords/Search Tags:Pervasive computing, DSS, Data utility, Resource availability, Availability awareness, Decision support, Architecture
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