The performance of a program can sometimes greatly improve if it was known in advance the features of the input the program is supposed to process, the actual operating parameters it is supposed to work with, or the specific environment it is to run on. However, this information is typically not available until too late in the program’s operation to take advantage of it. This is especially true for simulation algorithms, which are sensitive to this late-arriving information, and whose role in the solution of decision-making, inference and valuation problems is crucial. To overcome this limitation we need to provide the flexibility for a program to adapt its behaviour to late-arriving information once it becomes available. In this thesis, I study three adaptation mechanisms: run-time code generation, model-specific (quasi) Monte Carlo sampling and dynamic computation offloading, and evaluate their benefits on Monte Carlo algorithms. First, run-time code generation is studied in the context of Monte Carlo algorithms for time-series filtering in the form of the Input-Adaptive Kalman filter, a dynamically generated state estimator for non-linear, non-Gaussian dynamic systems. The second adaptation mechanism consists of the application of the functional-ANOVA decomposition to generate model-specific QMC-samplers which can then be used to improve Monte Carlo-based integration. The third adaptive mechanism treated here, dynamic computation offloading, is applied to wireless communication management, where network conditions are assessed via option valuation techniques to determine whether a program should offload computations or carry them out locally in order to achieve higher run-time (and correspondingly battery-usage) efficiency. This ability makes the program well suited for operation in mobile environments. At their core, all these applications carry out or make use of (quasi) Monte Carlo simulations on dynamic Bayesian networks (DBNs). The DBN formalism and its associated simulation-based algorithms are of great value in the solution to problems with a large uncertainty component. This characteristic makes adaptation techniques like those studied here likely to gain relevance in a world where computers are endowed with perception capabilities and are expected to deal with an ever-increasing stream of sensor and time-series data.

Mobile ad hoc networks (MANETs) can be formed dynamically without the support of any existing infrastructure or any centralized administration. They consist of heterogeneous mobile nodes which are powered by batteries, move arbitrarily and are connected by wireless links. Battery energy limitation is one of the main challenges in the MANETs. Several hardware and software based techniques have been proposed in this field. Most of the previous studies have considered only the energy minimization of individual nodes and disregarded the overall network lifetime. Topology management is another important problem in MANETs, in this sense / several new computing paradigms have been developed by the researchers, and the topology management has not been studied clearly in most of these models. In this study, we propose two new techniques that deal with the topology management in order to facilitate the nodes&rsquo / cooperation towards energy saving. The developed computing model considers heterogeneous mobile nodes. A node that faces shortage in its resources (energy and processing capability) sends its work to one of the nearby devices which is able to execute the work. In addition, we propose two algorithm for dynamic and two for static task scheduling, to prolong the network life time. Comprehensive experiments showed that the proposed schemes achieve a significant improvement in the network lifetime while simultaneously reducing the energy consumption and time delay for each task.

While much attention has been paid to the usability of desktop computers, mobile com- puters are quickly becoming the dominant platform. Because mobile computers may be used in nearly any situation--including while the user is actually in motion, or performing other tasks--interfaces designed for stationary use may be inappropriate, and alternative interfaces should be considered. In this dissertation I consider the idea of microinteractions--interactions with a device that take less than four seconds to initiate and complete. Microinteractions are desirable because they may minimize interruption; that is, they allow for a tiny burst of interaction with a device so that the user can quickly return to the task at hand. My research concentrates on methods for applying microinteractions through wrist- based interaction. I consider two modalities for this interaction: touchscreens and motion- based gestures. In the case of touchscreens, I consider the interface implications of making touchscreen watches usable with the finger, instead of the usual stylus, and investigate users' performance with a round touchscreen. For gesture-based interaction, I present a tool, MAGIC, for designing gesture-based interactive system, and detail the evaluation of the tool.

The increasing ubiquity of networked mobile devices such as cell phones and PDAs has created new opportunities for the transmission and display of multimedia content. However, any mobile device has inherent resource constraints: low network bandwidth, small screen sizes, limited input methods, and low commitment viewing. Mobile systems that provide information display and access thus need to mitigate these various constraints. Despite progress in information retrieval and content recommendation, there has been less focus on issues arising from a network-oriented and mobile perspective. This dissertation investigates a coordinated design approach to networked multimedia on mobile devices, and considers the abovementioned system perspectives. Within the context of accessing news video on mobile devices, the goal is to provide a cognitively palatable stream of videos and a seamless, low-latency user experience. Mixed-initiative---a method whereby intelligent services and users collaborate efficiently to achieve the user's goals, is the cornerstone of the system design and integrates user relevance feedback with a content recommendation engine and a content- and network-aware video buffer prefetching technique. These various components have otherwise been considered independently in other prior system designs. To overcome limited interactivity, a mixed-initiative user interface was used to present a sequence of news video clips to the user, along with operations to vote-up or vote-down a video to indicate its relevance. On-screen gesture equivalents of these operations were also implemented to reduce user interface elements occupying the screen. Semantic relevancy was then improved by extracting and indexing the content of each video clip as text features, and using a Na"ive Bayesian content recommendation strategy that harnessed the user relevance feedback to tailor the subsequent video recommendations. With the system's knowledge of relevant videos, a content-aware video buffer prefetching scheme was then integrated, using the abovementioned feedback to lower the user perceived latency on the client-end. As an information retrieval system consists of many interacting components, a client-server video streaming model is first developed for clarity and simplicity. Using a CNN news video clip database, experiments were then conducted using this model to simulate user scenarios. As the aim of improving semantic relevancy sometimes opposes user interface tools for interactivity and user perceived latency, a quantitative evaluation was done to observe the tradeoffs between bandwidth, semantic relevance, and user perceived latency. Performance tradeoffs involving semantic relevancy and user perceived latency were then predicted. In addition, complementary human user subjective tests are conducted with actual mobile phone hardware running on the Google Android platform. These experiments suggest that a mixed-initiative approach is helpful for recommending news video content on a mobile device for overcoming the mobile limitations of user interface tools for interactivity and client-end perceived latency. Users desired interactivity and responsiveness while viewing videos, and were willing to sacrifice some content relevancy in order gain lower perceived latency. Recommended future work includes expanding the content recommendation to incorporate viewing data from a large population, and the creation of a global hybrid content-based and collaborative filtering algorithm for better results. Also, based on existing user behaviour, users were reluctant to provide more input than necessary. Additional user experiments can be designed to quantify user attention and interest during video watching on a mobile device, and for better definition and incorporation of implicit user feedback.

Construction has a higher injury and fatality rate than most of the other industries. Given this situation, existing research has studied various issues and factors affecting construction safety management and has attempted to use all available methods to improve the construction safety performance. However, the construction accident rate remains among the highest in the United States and the world. The primary objective of this research is to advance autonomous proximity monitoring and hence provide a safer environment for construction workers. In particular, I seek to advance current evaluations of proximity warning technologies to a more robust engineering approach to the design and deployment of autonomous safety monitoring systems. The contributions of the research are demonstrated through specifications, deployments, and testing of proximity monitoring systems for crane loads and falling from height. My research advances current knowledge in three areas. First, I develop specifications for proximity safety monitoring in a sensed environment, built from existing guidelines and expert interviews. Second, I translate the specifications to computer interpretable rules and deploy them in a distributed computing environment. This demonstrates the feasibility of a systems approach and reusability of components to speed deployment. Third, I evaluate the accuracy of the specifications and systems under imperfect data. I further evaluate some approaches to dealing with imperfect data. Collectively, these advances move existing proximity warning research from evaluation of specific systems to an engineering approach to development and deployment of distributed systems with reusable components that explicitly treats imperfect data. / text

Šiame darbe analizuojama mobilaus ryšio sistema. Yra tariama, jog tinkle egzistuoja dviejų tipų įrenginiai: mobilūs ir fiksuoti. Fiksuoti įrenginiai yra visados įjungti ir prijungti prie tinklo. Fiksuoti įrenginiai, tai mobiliosios palaikymo stotys (MPS) ir duomenų bazė. Mobilūs įrenginiai (mobilūs kompiuteriai) gauna duomenis iš duomenų bazės, tarpininkaujant palaikymo stotims. Mobilūs kompiuteriai prisijungia ir persijungia prie skirtingų MPS, priklausomai nuo jų skleidžiamo signalo stiprumo. Visi veiksmai atliekami nuosekliai, nepertraukiant galutinio vartotojo darbo. Kuriant tokių sistemų programinius modelius pirmiausia reikia jas išanalizuoti ir suformalizuoti. Viena iš formalizavimo kalbų – PLA, neseniai buvo išplėsta, kad gal���tų aprašyti dinamines sistemas. Šiame darbe supažindinama su naujai išplėsta formalizavimo kalba (dynPLA). Ji naudojama mobilaus ryšio sistemos specifikavimui bei tikrinama ar formalizavimo kalbos išplėtimų užtenka aprašyti minėtąją sistemą. Pasiūlyti dynPLA formalizavimo kalbos patobulinimai bei pateiktas sistemos modelio specifikacijos pavyzdys. / The mobile computing system will be analyzed in this work. It is assumed that network consists of two types of devices: mobile and fixed. Fixed devices are always on and always connected to the network. These devices include, but are not limited to database servers and mobile support stations (MSS). Mobile devices access data from database. They connect and reconnect to different MSS depending on the signal strength. All of this is done seamlessly to the end user and the data transfer is not disturbed. When planning to implement such system in programming language, the first step is analyzing and formalizing it. One of the formalization languages – PLA, was recently extended for the sole purpose of formalization of dynamic systems. This work, “The Usage of dynPLA Formalism for Modeling of Mobile Computing System” covers the usage of new extended formalization language (dynPLA) for mobile computing system, analyzing if dynPLA extensions are sufficient for formalizing the said system. Also some improvements for the dynPLA formalization language will be suggested and the example of the mobile computing system will be given.

An ad-hoc network is a collection of mobile nodes (wireless communication devices) that transmit data over systems that do not require any centralized control, such as that found in cellular networks. This makes ad-hoc networks suitable for military type applications, since there is no need for an established backbone infrastructure and hence no single-point-of-failure. However, other uses of ad-hoc systems include search and rescue missions, law enforcement operations, commercial and educational communication of laptop (and other handheld device) data, as well as in the transmission of environmental sensor information. The mobile ad-hoc concept brings many design challenges. The dynamic freedom of movement from mobile nodes causes random, sometimes rapidly time changing topologies, which are inappropriate for use through traditional wired protocols. In addition, wireless networks generally contain greater bandwidth, processing and power constraints than their wired counterparts, since they are implemented on embedded mobile, handheld devices. Thus, a different approach is needed in the wireless network domain. This has resulted in wireless routing protocols employing adaptive, multi-hop, distributed methodologies in which each node additionally acts as a router for each of its neighbouring nodes, in order to achieve a large degree of network connectivity. However, due to the broadcast nature of wireless transmissions, ad-hoc systems contain a point-to- multipoint communication architecture, making it well suited to multi-path traffic. One such application is in multicasting, which sends data from one source to two (or more) destinations. But, due to the shared characteristics of the communication channel, such traffic may cause multiple contentions and collisions to occur, which will degrade the efficiency and performance of a protocol. This dissertation examines these different design tradeoffs through the use of a freely available simulation package, known as NS-2 (Network Simulator - version 2). In addition, a novel routing protocol, known as LAMP (Location Aided Multicasting Protocol), is developed to handle time-bounded audio information, which is employed in a network that consists of sixteen commercial handheld devices. LAMP utilizes a destination-sequenced, next-hop routing table to forward multicast data. Since mobility causes neighbouring nodes to continually change, next-hop links need to be periodically updated. But, between each update period, a next-hop link may become broken. Thus, if a packet is required to be routed, for which its' next-hop link is unknown, LAMP reverts to a localized location aided flood to find a path to that destination. However, since flooding causes network congestion, it is only employed when its' table forwarding scheme fails. Results have shown that LAMP improves packet delivery ratios by up to 5% over exisiting flood-limiting schemes: Furthermore, LAMP has been shown to be comparable to leading schemes, even when employed to route data to a single source-destination pair. / Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.

Microprocessor architecture has changed significantly since Intel Corporation developed the first commercial computer chip in the 1970s. The modern processors are much smaller and more powerful than their predecessors. Yet, in the mobile computing era the market demands for smaller, faster, cooler, and more power-efficient CPUs that could provide greater performance-per-watt results. In this dissertation, we address some of the shortcomings in conventional microprocessor designs and discuss possible means of alleviating them. First, we investigate the energy dissipation in Branch Target Buffer (BTB), a commonly present component in branch prediction unit. Our primary contribution is a speculative allocation technique to improve BTB energy consumption. In this technique, a new on-chip structure predicts the BTB activity and dynamically eliminates unnecessary accesses. Next, we formulate a quantitative metric to analyze the trade-off between processor energy efficiency and cache energy consumption. We investigate the upper bound energy and latency budget available for alternative data and instruction cache enhancements. This dissertation concludes with a novel approach to increase processors’ performance by reducing data cache miss rate. We employ a speculative technique to bridge the performance gap between the common Least Recently Used (LRU) replacement algorithm and the optimal replacement policy. We evaluate the non-optimal decisions made by the LRU algorithm and provide a taxonomy of mistakes, which will aid to identify and avoid similar decisions in future incidents.

The performance of a program can sometimes greatly improve if it was known in advance the features of the input the program is supposed to process, the actual operating parameters it is supposed to work with, or the specific environment it is to run on. However, this information is typically not available until too late in the program’s operation to take advantage of it. This is especially true for simulation algorithms, which are sensitive to this late-arriving information, and whose role in the solution of decision-making, inference and valuation problems is crucial. To overcome this limitation we need to provide the flexibility for a program to adapt its behaviour to late-arriving information once it becomes available. In this thesis, I study three adaptation mechanisms: run-time code generation, model-specific (quasi) Monte Carlo sampling and dynamic computation offloading, and evaluate their benefits on Monte Carlo algorithms. First, run-time code generation is studied in the context of Monte Carlo algorithms for time-series filtering in the form of the Input-Adaptive Kalman filter, a dynamically generated state estimator for non-linear, non-Gaussian dynamic systems. The second adaptation mechanism consists of the application of the functional-ANOVA decomposition to generate model-specific QMC-samplers which can then be used to improve Monte Carlo-based integration. The third adaptive mechanism treated here, dynamic computation offloading, is applied to wireless communication management, where network conditions are assessed via option valuation techniques to determine whether a program should offload computations or carry them out locally in order to achieve higher run-time (and correspondingly battery-usage) efficiency. This ability makes the program well suited for operation in mobile environments. At their core, all these applications carry out or make use of (quasi) Monte Carlo simulations on dynamic Bayesian networks (DBNs). The DBN formalism and its associated simulation-based algorithms are of great value in the solution to problems with a large uncertainty component. This characteristic makes adaptation techniques like those studied here likely to gain relevance in a world where computers are endowed with perception capabilities and are expected to deal with an ever-increasing stream of sensor and time-series data.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.