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<p>    </p> <p>An energy harvesting system (EHS) provides the intriguing possibility of battery-less computing and enables various applications such as wearable, industrial or environmental sensors, and im- plantable medical devices. The biggest challenge of EHS is the instability of energy sources (e.g., Wi-Fi, solar, thermal energy, etc.) which causes unpredictable and frequent power outages. To address the challenge, existing works introduce software-based and hardware-based power failure recovery solutions that ensure program correctness across a power outage. However, they cause a significant performance overhead without providing the high quality of service in reality, and suffer from a reliability issue. In this dissertation, we address the limitations of recovery solutions across the system stack, from the compiler-directed approach and run-time systems to hardware mechanisms, and demonstrate the effectiveness of the approaches using real EHS platforms and simulators. We first present software-based recovery solutions by leveraging compiler support. We develop a compiler-directed solution built upon commodity EHS platform that can achieve 3X speedup compared to the software-based state-of-the-art solution. We also introduce a compiler optimization technique that can cooperate with run-time systems and hardware support, achieving 8X speedup compared to the software-based solution. We then present hardware-based recov- ery solutions by leveraging compiler and hardware support. We develop an architecture/compiler co-design solution that re-purposes existing hardware components in a core for power failure spec- ulative execution, a new speculation paradigm, and leverages a novel compiler analysis for cor- rect power failure recovery. Our result highlights 2 ∼ 3x performance improvement compared to the hardware-based state-of-the-art solution without requiring hardware modification. Next, we present a new cache design for EHS that can achieve cost-effective, high-performance intermit- tent computing. According to experimental results, the new cache design outperforms the state- of-the-art cache scheme by 4X and reduces the hardware cost by 90%. Finally, we present an operating system (OS)-driven solution to address a reliability problem on EHS devices while all existing works are vulnerable, causing the wrong recovery across power failure. Our experiments demonstrate that the solution causes less than 1% run-time overhead and successfully addresses the reliability problem without compromising correct power failure recovery. </p>

abstract: Recently, nanostructured metamaterials have attracted lots of attentions due to its tunable artificial properties. In particular, nanowire/nanohole based metamaterials which are known of the capability of large area fabrication were intensively studied. Most of the studies are only based on the electrical responses of the metamaterials; however, magnetic response, is usually neglected since magnetic material does not exist naturally within the visible or infrared range. For the past few years, artificial magnetic response from nanostructure based metamaterials has been proposed. This reveals the possibility of exciting resonance modes based on magnetic responses in nanowire/nanohole metamaterials which can potentially provide additional enhancement on radiative transport. On the other hand, beyond classical far-field radiative heat transfer, near-field radiation which is known of exceeding the Planck’s blackbody limit has also become a hot topic in the field. This PhD dissertation aims to obtain a deep fundamental understanding of nanowire/nanohole based metamaterials in both far-field and near-field in terms of both electrical and magnetic responses. The underlying mechanisms that can be excited by nanowire/nanohole metamaterials such as electrical surface plasmon polariton, magnetic hyperbolic mode, magnetic polariton, etc., will be theoretically studied in both far-field and near-field. Furthermore, other than conventional effective medium theory which only considers the electrical response of metamaterials, the artificial magnetic response of metamaterials will also be studied through parameter retrieval of far-field optical and radiative properties for studying near-field radiative transport. Moreover, a custom-made AFM tip based metrology will be employed to experimentally study near-field radiative transfer between a plate and a sphere separated by nanometer vacuum gaps in vacuum. This transformative research will break new ground in nanoscale radiative heat transfer for various applications in energy systems, thermal management, and thermal imaging and sensing. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2017

Energy harvesting (EH) nodes, which harvest energy from the environment in order to communicate over a wireless link, promise perpetual operation of wireless networks. The primary focus of the communication system design shifts from being as energy conservative as possible to judiciously handling the randomness in the energy harvesting process in order to enhance the system performance. This engenders a significant redesign of the physical and multiple access layers of communication. In this thesis, we address the problem of maximizing the throughput of a system that consists of rate-adaptive EH nodes that transmit data to a common sink node. We consider the practical case of discrete rate adaptation in which a node selects its transmission power from a set of finitely many rates and adjusts its transmit power to meet a bit error rate (BER) constraint. When there is only one EH node in the network, the problem involves determining the rate and power at which the node should transmit as a function of its channel gain and battery state. For the system with multiple EH nodes, which node should be selected also needs to be determined. We first prove that the energy neutrality constraint, which governs the operation of an EH node, is tighter than the average power constraint. We then propose a simple rate and power adaptation scheme for a system with a single EH node and prove that its throughput approaches the optimal throughput arbitrarily closely. We then arrive at the optimal selection and rate adaptation rules for a multi-EH node system that opportunistically selects at most one node to transmit at any time. The optimal scheme is shown to significantly outperform other ad hoc selection and transmission schemes. The effect of energy overheads, such as battery storage inefficiencies and the energy required for sensing and processing, on the transmission scheme and its overall throughput is also analytically characterized. Further, we show how the time and energy overheads incurred by the opportunistic selection process itself affect the adaptation and selection rules and the overall system throughput. Insights into the scaling behavior of the average system throughput in the asymptotic regime, in which the number of nodes tend to infinity, are also obtained. We also optimize the maximum time allotted for selection, so as to maximize the overall system throughput. For systems with EH nodes or non-EH nodes, which are subject to an average power constraint, the optimal rate and power adaptation depends on a power control parameter, which hitherto has been calculated numerically. We derive novel asymptotically tight bounds and approximations for the same, when the average rate of energy harvesting is large. These new expressions are analytically insightful, computationally useful, and are also quite accurate even in the non-asymptotic regime when average rate of energy harvesting is relatively small. In summary, this work develops several useful insights into the design of selection and transmission schemes for a wireless network with rate-adaptive EH nodes.