As computing devices become more pervasive and integrated with our lives, it becomes useful for these devices to understand the environment which surrounds them and the activities of their users, so that they may adapt themselves to suit the circumstances and best assist their users. To accomplish this, it is necessary that these devices have a model for expressing and sharing contextual data which characterizes the state of the surroundings, the devices and people in an environment, and the relationships between each. This thesis describes a framework for managing the exchange of contextual data between devices and sensors with information about their shared environment, with other devices whose goals are to adapt their behaviour to best suit the circumstances. This function supports the greater goal of implementing a pervasive computing environment. We identify three roles in context sharing: Context Providers which are sources of contextual data such as sensors; Context Consumers which are applications which use contextual data to adapt themselves; and Context Hosts which act as intermediaries facilitating the exchange of data and provide a proxy host for contextual data on behalf of Context Providers. This framework includes protocols to facilitate data exchange between each with considerations for the security and data privacy. This thesis also outlines an extensible model for defining and expressing contextual data and related meta data. The context model can be passed among the context sharing actors to communicate state and relationships between entities in the working environment. / Thesis (Master, Computing) -- Queen's University, 2012-09-07 11:42:42.117

The dream of pervasive computing is slowly becoming a reality. A number of projects around the world are constantly contributing ideas and solutions that are bound to change the way we interact with our environments and with one another. An essential component of the future is a software infrastructure that is capable of supporting interactions on scales ranging from a single physical space to intercontinental collaborations. Such infrastructure must help applications adapt to very diverse environments and must protect people's privacy and respect their personal preferences. In this paper we indicate a number of limitations present in the software infrastructures proposed so far (including our previous work). We then describe the framework for building an infrastructure that satisfies the abovementioned criteria. This framework hinges on the concepts of delegation, arbitration and high-level service discovery. Components of our own implementation of such an infrastructure are presented.

Wireless devices and their services are becoming increasingly important for many people¡¦s lives. The services provided by these mobile devices enable users to work without space or time limitation. However, while these applications allow users to record and retrieve information about tasks and data, the relationships between tasks and data are left out. However, we have observed that many of people¡¦s daily activities are not independent, and they are likely to be process-oriented. In this thesis, we develop a personal workflow model that is used to capture the requirements of personal processes. This model also includes a set of primitive operations that can be used to express queries on personal processes. The algebraic properties about these operations and how to optimize queries comprised of these operations are studied. Based on these operations, we propose an SQL-like query language to ease users¡¦ query expressions. Besides, to actively remind the mobilers the right things to do at the right place and the right time, we propose a rule model that resembles event-condition-action (ECA) rules proposed for active database systems. All of the proposed features except for the rule model are implemented on Palm Pilot PDAs.

Pervasive Computing presents an exciting realm where intelligent devices interact within the background of our environments to create a more intuitive experience for their human users. We demonstrate enabling context-awareness through our creation of a standardized context-management framework. Our framework moves towards device intelligence by supporting context-awareness. Context-awareness is what gives devices the ability to understand and exchange information about each other. Context information is used to determine device purpose, capabilities, location, current state, and other properties. Several elements are required in order to achieve context-awareness, including a suitable ontology, a context model, and a middleware platform upon which to implement the context model. In this work, a complete context-management framework is presented and evaluated. We propose our own ontology specification and context model, and implement a middleware using the Web Services Distributed Management (WSDM) interoperability standard. / Thesis (Master, Computing) -- Queen's University, 2008-09-09 14:51:30.242

Wireless and pervasive computing research continues to study ways the Internet of Things (IoT)<br />can make lives easier and more productive. Areas of interest include advances in new<br />architectures and frameworks that support large-scale IoT deployments beyond research<br />prototypes, simple and inexpensive human-to-device and device-to-device interfaces, and user<br />decision making support with opportunistic information services.<br /><br />This dissertation investigates the design and implementation of a general-purpose framework<br />upon which IoT and opportunistic computing (OC) systems can be built.<br /><br />The result of this work is Pebbles and Urns (P&U), a casually accessible system designed to<br />deliver information to a person that is pertinent and beneficial to them with respect to their<br />current activity, location and other contexts. P&U is a proximity-based information delivery<br />framework that leverages a simple, inexpensive tangible interface and context-rich, physicallysituated,<br />distributed information repositories. By its proposed use of enforced proximity, local<br />context, and location-specific services, P&U can support the situated interaction between user<br />and place.<br /><br />The P&U framework is based on a layered architecture consisting of an isolated physical<br />communication layer, a data repository supporting opportunistic service composition and<br />delivery, and a controller/interface providing user feedback. Serving as a potential IoT design<br />pattern, P&U application developers can use the framework API\'s and software tools to build<br />and deploy P&U systems.<br /><br />As validation of this work, P&U prototypes are constructed using the framework, API\'s and<br />software tools. The prototypes are based on use cases depicting a person engaged in the day-today<br />activities of attending class, going to the gym and grocery shopping. Performance<br />measurements are performed on the prototypes profiling core components of the framework.<br />Results indicate proper functioning of P&U tangible interfaces, communication connections,<br />service request and delivery, and internal framework operations.<br /><br />Contributions of this research include a general-purpose framework, a simple IoT interface and<br />an opportunistic engine. / Ph. D.

This thesis focuses on an Agent-Based Service-Oriented approach to evolving legacy system into a Pervasive Computing environment. The methodology consists of multiple phases: using reverse engineering techniques to comprehend and decompose legacy systems, employing XML and Web Services to transform and represent a legacy system as pervasive services, and integrating these pervasive services into pervasive computing environments with agent based integration technology. A legacy intelligent building system is used as a case study for experiments with the approach, which demonstrates that the proposed approach has the ability to evolve legacy systems into pervasive service environments seamlessly. Conclusion is drawn based on analysis and further research directions are also discussed.

Hur kan svårighetsprogression användas i skapandet av Puzzlehunts med syfte att uppnå en ökad upplevd känsla av flow hos spelaren? Denna frågeställning behandlas i uppsatsen och problemet som måste lösas är hur man kan bygga upp en ackumulerad kunskap om något vars syfte är att hela tiden tvinga dig att hitta nya lösningar på problem. I mer traditionella spel kan upprepning lära spelaren hur spelmekaniken fungerar. I puzzlehunts kan upprepning av spelmekanik inte användas eftersom målet för varje pussel är att hitta mekaniken som löser problemet. Uppsatsen visar att man genom inlärning av hur man skall tänka för att hitta lösningarna till pusslen kan bygga upp en ackumulerad kunskap hos spelaren och därmed även ha en svårighetsprogression och öka upplevd nivå av flow hos spelaren.

Mobile devices are generally less powerful and more resource constrained than their desktop counterparts are, yet many of the applications that are of the most value to users of mobile devices are resource intensive and difficult to support on a mobile device. Applications such as games, video playback, image processing, voice recognition, and facial recognition are resource intensive and often exceed the limits of mobile devices. Cyber foraging is an approach that allows a mobile device to discover and utilize surrogate devices present in the local environment to augment the capabilities of the mobile device. Cyber foraging has been shown to be beneficial in augmenting the capabilities of mobile devices to conserve power, increase performance, and increase the fidelity of applications. The cyber foraging scheduler determines what operation to execute remotely and what surrogate to use to execute the operation. Virtually all cyber foraging schedulers in use today utilize historical data in the scheduling algorithm. If historical data about a surrogate is unavailable, execution history must be generated before the scheduler's algorithm can utilize the surrogate. The period between the arrival time of a surrogate and when historical data become available is called the cold-start state. The cold-start state delays the utilization of potentially beneficial surrogates and can degrade system performance. The major contribution of this research was the extension of a historical-based prediction algorithm into a low-overhead estimation-enhanced algorithm that eliminated the cold-start state. This new algorithm performed better than the historical and random scheduling algorithms in every operational scenario. The four operational scenarios simulated typical use-cases for a mobile device. The scenarios simulated an unconnected environment, an environment where every surrogate was available, an environment where all surrogates were initially unavailable and surrogates joined the system slowly over time, and an environment where surrogates randomly and quickly joined and departed the system. One future research possibility is to extend the heuristic to include storage system I/O performance. Additional extensions include accounting for architectural differences between CPUs and the utilization of Bayesian estimates to provide metrics based upon performance specifications rather than direct

In this submission, five articles are presented examining one theme: diagnosis of autism spectrum disorders (ASD) in children. Three articles provides perspectives on various social and medical factors that influence the diagnosis of ASD, and the others examine social and behavioural outcomes for children diagnosed with ASD. One article provides an in depth examination of the dilemmas of diagnosis from a parental perspective. The research utilized both qualitative and quantitative methods. A secondary analysis of a longitudinal birth cohort study revealed that there were a number of children who had autistic traits equally severe as those with clinical diagnosis. Further analysis exposed a possible gender bias in diagnosis. Outcomes for children with ASD diagnoses were worse than for those without diagnoses but with comparable behaviours as preschoolers. ASD diagnosis apparently had no positive effect on the developmental trajectory of prosocial behaviour. The implications of these results are discussed. Analysis of qualitative data collected in semi-structured interviews with parents of both diagnosed and undiagnosed children exposed dilemmas faced by parents as they contemplated an ASD diagnosis and highlighted parental action to de-stigmatise the condition after diagnosis had been applied. The body of work as a whole falls at the junction of clinical and educational psychology, developmental psychology, social psychology, social psychiatry, sociology and epidemiology. It draws attention to a number of social processes that contribute to ASD diagnosis. Overall, it is argued, the work supports the conceptualisation of ASD as both a biologically and socially determined condition.

This investigation was concerned with the potential effectiveness of systematic desensitization as a technique in the prevention of pervasive anxiety. It was hypothesized for investigatory purposes, that if two specific, potentially anxiety-evoking stimuli could be pre-desensitized, this would be strongly suggestive that pre-desensitization programs might also prove successful in the prevention of pervasive anxiety.