Context-aware computing utilizes information about users and/or their environments in order to provide relevant information and services. To date, however, most context-aware applications only take advantage of contexts that can either be produced on the device they are running on, or on external devices that are known beforehand. While there are many application domains where sharing context is useful and/or necessary, creating these applications is currently difficult because there is no easy way for devices to share information without 1) explicitly directing them to do so, or 2) through some form of advanced user coordination (e.g., sharing credentials and/or IP addresses, installing and running the same software). This makes these techniques useful when the need to share context is known a priori, but impractical for the one time, opportunistic encounters which make up the majority of users’ lives. To address this problem, this thesis presents the Group Context Framework (GCF), a software framework that allows devices to form groups and share context with minimal prior coordination. GCF lets devices openly discover and request context from each other. The framework then lets devices intelligently and autonomously forms opportunistic groups and work together without requiring either the application developer or the user to know of these devices beforehand. GCF supports use cases where devices only need to share information once or spontaneously. Additionally, the framework provides standardized mechanisms for applications to collect, store, and share context. This lets devices form groups and work together, even when they are performing logically separate tasks (i.e., running different applications). Through the development of GCF, this thesis identifies the conceptual and software abstractions needed to support opportunistic groups in context-aware applications. As part of our design process, we looked at current contextsharing applications, systems, and frameworks, and developed a conceptual model that identifies the most common conditions that cause users/devices to form a group. We then created a framework that supports grouping across this entire model. Through the creation of four prototype systems, we show how the ability to form opportunistic groups of devices can increase users and devices’ access to timely information and services. Finally, we had 20 developers evaluate GCF, and verified that the framework supports a wide range of existing and novel use cases. Collectively, this thesis demonstrates the utility of opportunistic groups in context-aware computing, and highlights the critical challenges that need to be addressed to make opportunistic context sharing both practical and usable in real-world settings. The contributions of this thesis are: 1. A conceptual model, based on an analysis of prior literature, which describes the conditions under which users and/or devices form and work in groups. 2. An implementation of the Group Context Framework, which highlights the software abstractions and architecture needed to support all of the group types identified in our conceptual model. 3. A demonstration of the value of opportunistic groups in context aware computing, through the creation of four major systems and numerous smaller applications. 4. A validation of GCF’s robustness, through an examination of 65 ideas submitted by 20 developers. 5. An examination of the challenges associated with utilizing opportunistic groups in context-aware applications, based on our own experiences using GCF, as well as from issues raised by developers from academia and industry.

Recent technological advances have witnessed the rapid encroachment of computing systems into our social spaces. Their acceptance in these social spaces by other occupants, however, might be mostly contingent on their social appropriateness. Notions of social appropriateness might seem vague but even people who don’t act on this commonsense knowledge, and accord to social norms, can sometimes find themselves ostracized from society. It is reflected in behavior that supports a sense of successful engagement and connection. Such behavior communicates a desire to be accepted and a willingness to engage, as opposed to inappropriateness that conveys indifference, rejection or even danger. As social actors, how can systems improve their interactions with us in order to better succeed at their tasks? Perhaps, more interestingly, how might they even improve our communications with each other? In this thesis we describe a framework to identify opportunities to design systems that can begin to act appropriately in social settings, which we call Considerate Systems. It includes a design process and guidelines, which allows an interaction to be viewed from the perspectives of the user, system and task. It also includes an architecture that guides the addition of productive social responses to interactive systems. We demonstrate the utility of this framework by exploring two types of scenarios that impact social interactions in contrasting ways. Remote interactions (such as on a conference call) suffer from an impinging of social cues that people rely on while communicating. On the other hand, situated multitasking interactions (such as texting while driving) can easily overwhelm users and detract from their performance. The framework is applied towards the design of autonomous agents tackling problems endemic to such scenarios. We evaluate their success with respect to specific scenario goals. We conclude by noting that while the challenges of instilling computing systems with a sense of appropriateness seem daunting, our productive use of systems can be enhanced with them.

Com os avanços dos processos da microeletrônica temos dispositivos menores e com maior poder de computação e comunicação. Um Ambiente Pervasivo contém diferentes dispositivos, tais como sensores, atuadores, eletroeletrônicos e dispositivos móveis que interagem com a pessoa de forma natural ao conhecer o contexto. A diversidade de dispositivos e informações do Ambiente Pervasivo introduz um problema de interoperabilidade. Um Ambiente Pervasivo é dinâmico devido à mobilidade do usuário, a variedade de dispositivos. Neste trabalho, é proposto um modelo semântico de contexto para permitir interoperabilidade e fornecer suporte ao dinamismo do Ambiente Pervasivo. O modelo proposto contém características da modelagem de contexto realizadas por trabalhos anteriores, assim como sua integração com a modelagem de preferências das pessoas, políticas de privacidade e serviços. Verificou-se que o modelo de contexto proposto é adequado mediante sua aplicação em um Estudo de Caso e mediante testes realizados. Mostra-se que a modelo de contexto utilizado ontologias e Serviços Web Semânticos permite tratar com informação incompleta e inconsistente, bem como fornece suporte na interoperabilidade e ao dinamismo do Ambiente Pervasivo. / Advances in microelectronic processes have allowed smaller devices with more computation and communication power. Pervasive environment contains different devices like electronic sensor, actuators and mobile devices which interact with the person naturally after the context is known. The device and information diversity introduce an interoperability problem. Pervasive environments are dynamics because of user\'s mobility and a variety of devices. In this work, we propose a context model to allow interoperability and to give support to pervasive environment dynamism. The proposed model contains features of context modeling developed in previous works, as well as, their integration with the modeling of the people\'s preferences, privacy policies and services. It was verified that the context model is appropriate by their application in a Case Study and by accomplished tests. It is shown that the model of context using ontologies and Semantic Web Services allow us to work with inconsistent and incomplete information, as well as gives support to interoperability and dynamism of the Pervasive Environment.

Com os avanços dos processos da microeletrônica temos dispositivos menores e com maior poder de computação e comunicação. Um Ambiente Pervasivo contém diferentes dispositivos, tais como sensores, atuadores, eletroeletrônicos e dispositivos móveis que interagem com a pessoa de forma natural ao conhecer o contexto. A diversidade de dispositivos e informações do Ambiente Pervasivo introduz um problema de interoperabilidade. Um Ambiente Pervasivo é dinâmico devido à mobilidade do usuário, a variedade de dispositivos. Neste trabalho, é proposto um modelo semântico de contexto para permitir interoperabilidade e fornecer suporte ao dinamismo do Ambiente Pervasivo. O modelo proposto contém características da modelagem de contexto realizadas por trabalhos anteriores, assim como sua integração com a modelagem de preferências das pessoas, políticas de privacidade e serviços. Verificou-se que o modelo de contexto proposto é adequado mediante sua aplicação em um Estudo de Caso e mediante testes realizados. Mostra-se que a modelo de contexto utilizado ontologias e Serviços Web Semânticos permite tratar com informação incompleta e inconsistente, bem como fornece suporte na interoperabilidade e ao dinamismo do Ambiente Pervasivo. / Advances in microelectronic processes have allowed smaller devices with more computation and communication power. Pervasive environment contains different devices like electronic sensor, actuators and mobile devices which interact with the person naturally after the context is known. The device and information diversity introduce an interoperability problem. Pervasive environments are dynamics because of user\'s mobility and a variety of devices. In this work, we propose a context model to allow interoperability and to give support to pervasive environment dynamism. The proposed model contains features of context modeling developed in previous works, as well as, their integration with the modeling of the people\'s preferences, privacy policies and services. It was verified that the context model is appropriate by their application in a Case Study and by accomplished tests. It is shown that the model of context using ontologies and Semantic Web Services allow us to work with inconsistent and incomplete information, as well as gives support to interoperability and dynamism of the Pervasive Environment.

Demand response is one of the critical technologies necessary for allowing large-scale penetration of intermittent renewable energy sources in the electric grid. Data centers are especially attractive candidates for providing flexible, real-time demand response services to the grid because they are capable of fast power ramp-rates, large dynamic range, and finely-controllable power consumption. This thesis makes a contribution toward implementing load shaping with server clusters through a detailed experimental investigation of three broadly-applicable datacenter workload scenarios. We experimentally demonstrate the eminent feasibility of datacenter demand response with a distributed video transcoding application and a simple distributed power controller. We also show that while some software power capping interfaces performed better than others, all the interfaces we investigated had the high dynamic range and low power variance required to achieve high quality power tracking. Our next investigation presents an empirical performance evaluation of algorithms that replace arithmetic operations with low-level bit operations for power-aware Big Data processing. Specifically, we compare two different data structures in terms of execution time and power efficiency: (a) a baseline design using arrays, and (b) a design using bit-slice indexing (BSI) and distributed BSI arithmetic. Across three different datasets and three popular queries, we show that the bit-slicing queries consistently outperform the array algorithm in both power efficiency and execution time. In the context of datacenter power shaping, this performance optimization enables additional power flexibility -- achieving the same or greater performance than the baseline approach, even under power constraints. The investigation of read-optimized index queries leads up to an experimental investigation of the tradeoffs among power constraint, query freshness, and update aggregation size in a dynamic big data environment. We compare several update strategies, presenting a bitmap update optimization that allows improved performance over both a baseline approach and an existing state-of-the-art update strategy. Performing this investigation in the context of load shaping, we show that read-only range queries can be served without performance impact under power cap, and index updates can be tuned to provide a flexible base load. This thesis concludes with a brief discussion of control implementation and summary of our findings.

We present the high level (VHDL) modeling and high level synthesis of an ASIC (TOUR NAVIGATOR) for a portable hand held device - a tour guide. The tour guide is based on location-aware mobile computing, which gives the information of the current location to the user. The TOUR NAVIGATOR designed in this work is interfaced with off-the-shelf components to realise the tour guide system. The current location is given by an on-board GPS receiver chip. The TOUR NAVIGATOR is a search and play module which interfaces with the flash memory, GPS receiver and the audio codec. The functionality of the TOUR NAVIGATOR is to search the flash memory for audio data corresponding to the current GPS co-ordinate, which is an input to the TOUR NAVIGATOR. The look-up table containing the GPS coordinates and the corresponding audio files are loaded into the flash memory, where in each GPS entry in the table is indexed by the co-ordinates, and an audio file that contains information about the locations is associated with it. When there is a match, the audio file is streamed to the codec. The functionality of the interface of the TOUR NAVIGATOR with the memory module is verified at the RTL using Cadence-NCLaunch. The layout implementation of the TOUR NAVIGATOR is done using an automatic place and route tool (Silicon Ensemble), which uses standard cells for the entire design. Leakage power reduction is done by introducing sleep transistors in the standard cells. The TOUR NAVIGATOR is put into a "sleep" mode when there is no operation of the tour guide, thus giving significant power savings.

<p>The purpose of the study is to explore the context, from the users’ perspective, in order to find relevant context parameters that can be useful in the development of the future context-aware technology. The goal is to find some of the context parameters relevant to the situated activity and investigate to what extent and in which way they influence the user in everyday planning activities.</p><p>The method used in the study was based on scenario descriptions. A total of 41 participants reported how they would have acted in the different situations and they also rated how important they believed the different context factors were in the situations. Analyses were made to reveal relationships between context factors and service properties used by the participants in the scenarios.</p><p>In the study several interesting relationships between context factors and the use of services were discovered. The level of urgency was in several situations considered to be important, and it was also found to have an impact on how the participants chose to communicate. The cost was introduced by the participants during the study. It seemed to be important; however, in situations with high urgency it became less important. The study revealed a potential relationship between the risk of disturbing the people in the vicinity and the effort to communicate quietly. Another interesting finding was the relationship between privacy and the choice of modality when communicating: voice-based services were avoided. Further, the importance of privacy and disturbance also appeared to have greater influence in non-anonymous situations than in anonymous.</p> / <p>Syftet med studien är att undersöka kontexten, utifrån användarens perspektiv, för att kunna hitta relevanta kontextfaktorer som kan vara användbara i utvecklingen av kontextmedveten teknologi. Målet är att finna kontextfaktorer som är relevanta för den pågående aktiviteten och undersöka i vilken utsträckning och på vilka sätt dessa faktorer påverkar användaren i de dagliga planeringsaktiviteterna.</p><p>Metoden som användes i studien baserades på scenariobeskrivningar. 41 stycken försöksdeltagare fick beskriva hur de skulle ha handlat i de olika situationerna och de fick också skatta hur viktiga de olika kontextfaktorerena var i situationerna. Analyser genomfördes för att finna samband mellan kontextfaktorer och egenskaper hos de tjänster som försöksdeltagarna använde sig av i scenarierna.</p><p>I studien upptäcktes en rad intressanta relationer mellan kontextfaktorer och användningen av tjänster. Exempelvis ansågs nivån av brådska vara betydelsefull i flera situationer och den verkade också ha inverkan på hur försöksdeltagarna valde att kommunicera. Försöksdeltagarna introducerade under studien kontextfaktorn kostnad. Kostnaden påverkade valet av tjänster men blev mindre betydande i situationer med stor brådska. Studien visade också på potentiella samband mellan risken att störa människor i sin omgivning och viljan att kommunicera tyst. En annan intressant upptäckt var sambandet mellan avskildhet och kommunikationssätt: röstbaserade tjänster undveks när andra människor fanns i närheten. Dessutom verkade det som om det var viktigare att värna om sin avskildhet och att inte störa andra i ickeanonyma situationer än i situationer där man var helt anonym.</p>

Context-aware computing is based on using knowledge about the current context. Interpretation of current context to an understandable knowledge is carried out by reasoning over context and in some cases by matching the current context with the desired context. In this thesis we concentrated on context matching issue in context-aware computing domain. Context matching can be done in various ways like it is done in other matching processes. Our matching approach is best matching in order to generate granular similarity results and not to be limited to Boolean values. We decided to use Ontology as the encoded domain knowledge for our matching method. Context matching method is related to the method that we represent context. We selected conceptual graphs to represent the context. We proposed a generic algorithm for context matching based on the ontological information that benefit from the conceptual graph theory and its advantages.

Current trends in society and technology make interruption a central human computer interaction problem. Many intelligent computer systems exist, but one that determines when best to interact with a user at appropriate times as s/he performs computer-based tasks does not. In this work, an Interaction Algorithm was designed, developed and evaluated that draws from a user model and real-time observations of the user’s actions as s/he works on computer-based tasks to determine ideal times to interact with the user. This research addresses the complex problem of determining the precise time to interrupt a user and how to best support him/her during and after the interruption task. Many sub-problems have been taken into account such as determining the task difficulty, the intent of the user as s/he is performing the task and how to incorporate personal user characteristics. This research is quite timely as the number of interruptions people experience on a daily basis has grown considerably over the last decade and this growth has not shown any signs of subsiding. Furthermore, with the exponential growth of mobile computing, interruptions are permeating the user experience. Thus, systems must be developed to manage interruptions by reasoning about ideal timings of interactions and determining appropriate notification formats. This research shed light on this problem as described below: 1. The algorithm developed uses a user model in its’ reasoning computations. Most of the research in this area has focused on task-based contextual information when designing systems that reason about interruptions. Researchers support additional work should be done in this area by including subjective preferences. 2. The algorithm’s performance is quite promising at 96% accuracy in several models created. 3. The algorithm was implemented using an advanced machine learning technology—an Adaptive Neural-Fuzzy Inference System—which is a novel contribution. 4. The algorithm developed does not rely on any user involvement. In other systems, users laboriously review video sessions after working with the system and record interruption annotations so that the system can learn. 5. This research shed light on reasoning about ideal interruption points for free-form tasks. Currently, this is an unsolved problem.

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