volving technology, has kept drawing a significant attention from both the computing industry and academia for nearly a decade.

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People are nomadic; traveling from place to place. As a user travels, he may need access to his digital information, including his data, applications, and settings. A convenient way to supply this access is to have the user carry that digital information in a portable computer such as a laptop or smart phone. As Moore's Law continues to operate, devices such as smart phones can easily perform the computing necessary for a user's work. Unfortunately, the amount of data a human can receive and convey through such devices is limited. To receive more information humans require more screen real estate. To transmit more information humans need rich input devices like mice and full-sized keyboards. To allow users to carry their digital information in a small device while maintaining opportunities for rich input, this research takes the approach of allowing users to carry a small portable device and then annex screens, keyboards, and mice whenever those devices are available in a user's environment. This research pursued the "carry it with you" paradigm first by building an ideal annexing framework which helps maximize the screen real estate while minimizing the resources—RAM, CPU, and wireless radio—consumed on the personal device. The resource consumption is demonstrated through a comparison with existing remote rendering technologies. Next, a privacy-aware framework was added to the annexing framework to help protect the user's sensitive data from damage and theft when he annexes a potentially malicious device. A framework like this has not existed before, and this research shows how the user's sensitive data is protected by this framework. Third, legacy machines and software are allowed to participate in the carry-it-with-you experience by scraping pixels from the user's existing applications and transmitting those pixels to an annexed display. Finally, when a user encounters a display space he does not own, but which he needs to control (e.g. by preventing anyone else from annexing it simultaneously, or by constraining each user to a different section of the display space), rather than forcing the user to learn and use control software supplied by the display, the user can bring his own control software and use it to enforce the user's desired control paradigm. This dissertation shows the carry-it-with-you paradigm is a powerful potential avenue which allows users to confidently use display spaces with varying configurations in an assortment of environments.

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No / Continuously identifying a user’s location context provides new opportunities to understand daily life and human behavior. Indoor location systems have been mainly based on WiFi infrastructures which consume a great deal of energy mostly due to keeping the user’s WiFi device connected to the infrastructure and network communication, limiting the overall time when a user can be tracked. Particularly such tracking systems on battery-limited mobile devices must be energy-efficient to limit the impact on the experience of using a phone. Recently, there have been a lot of studies of energy-efficient positioning systems, but these have focused on outdoor positioning technologies. In this paper, we propose a novel indoor tracking framework that intelligently determines the location sampling rate and the frequency of network communication, to optimize the accuracy of the location data while being energy-efficient at the same time. This framework leverages an accelerometer, widely available on everyday smartphones, to reduce the duty cycle and the network communication frequency when a tracked user is moving slowly or not at all. Our framework can work for 14 h without charging, supporting applications that require this location information without affecting user experience.

Wireless network devices, especially in ad hoc networks, are typically battery-powered. The growing need for energy efficiency in wireless networks, in general, and in mobile ad hoc networks (MANETs), in particular, calls for power enhancement features. The goal of this dissertation is to extend network lifetime by improving energy utilization in MANET routing. We utilize the ability of wireless network interface cards to dynamically change their transmission power, as well as the ability of wireless devices to read the remaining battery energy of the device to create a table of what we term "reluctance values," which the device uses to determine how to route packets. Choosing routes with lower reluctance values, on average and with time, leads to better utilization of the energy resources of the devices in the network. Our power-aware scheme can be applied to both reactive and proactive MANET routing protocols. As examples and to evaluate performance, the technique has been applied to the Dynamic Source Routing (DSR) protocol, a reactive routing protocol, and the Optimized Link State Routing (OLSR) protocol, a proactive routing protocol. Simulations have been carried out on large static and mobile networks. Results show improvements in network lifetime in static and certain mobile scenarios. Results also show better distribution of residual node energies at the end of simulations, which means that the scheme is balancing energy load more evenly across network nodes than the unmodified versions of DSR and OLSR. Average change in energy over time in the unmodified protocols show a steady increase with time, while the power-aware protocols show an increase in the beginning, then it levels for sometime before it starts to decrease. The power-aware scheme shows improvements in static and in coordinated mobility scenarios. In random mobility the power-aware protocols show no advantage over the unmodified protocols. / Ph. D.

As the number of processing cores contained in modern processors continues to increase, cache hierarchies are becoming more complex. This added complexity has the effect of increasing the potential cost of any cache misses on such architectures. When cache misses become more costly, minimizing them becomes even more important, particularly in terms of scalability concerns. In this thesis, we consider the problem of cache-aware real-time scheduling on multiprocessor systems. One avenue for improving real-time performance on multi-core platforms is task partitioning. Partitioning schemes statically assign tasks to cores, eliminating task migrations and reducing system overheads. Unfortunately, no current partitioning schemes explicitly consider cache effects when partitioning tasks. We develop the LWFG (Largest Working set size First, Grouping) cache-aware partitioning algorithm, which seeks to schedule tasks which share memory with one another in such a way as to minimize the total number of cache misses. LWFG minimizes cache misses by partitioning tasks that share memory onto the same core and by distributing the system's sum working set size as evenly as possible across the available cores. We evaluate the LWFG partitioning algorithm against several other commonly-used partitioning heuristics on a modern 48-core platform running ChronOS Linux. Our evaluation shows that in some cases, the LWFG partitioning algorithm increases execution efficiency by as much as 15% (measured by instructions per cycle) and decreases mean maximum tardiness by up to 60%. / Master of Science