Transiently Powered Computers

Demand for compact, easily deployable, energy-efficient computers has driven the development of general-purpose transiently powered computers (TPCs) that lack both batteries and wired power, operating exclusively on energy harvested from their surroundings. TPCs\u27 dependence solely on transient, harvested power offers several important design-time benefits. For example, omitting batteries saves board space and weight while obviating the need to make devices physically accessible for maintenance. However, transient power may provide an unpredictable supply of energy that makes operation difficult. A predictable energy supply is a key abstraction underlying most electronic designs. TPCs discard this abstraction in favor of opportunistic computation that takes advantage of available resources. A crucial question is how should a software-controlled computing device operate if it depends completely on external entities for power and other resources? The question poses challenges for computation, communication, storage, and other aspects of TPC design. The main idea of this work is that software techniques can make energy harvesting a practicable form of power supply for electronic devices. Its overarching goal is to facilitate the design and operation of usable TPCs. This thesis poses a set of challenges that are fundamental to TPCs, then pairs these challenges with approaches that use software techniques to address them. To address the challenge of computing steadily on harvested power, it describes Mementos, an energy-aware state-checkpointing system for TPCs. To address the dependence of opportunistic RF-harvesting TPCs on potentially untrustworthy RFID readers, it describes CCCP, a protocol and system for safely outsourcing data storage to RFID readers that may attempt to tamper with data. Additionally, it describes a simulator that facilitates experimentation with the TPC model, and a prototype computational RFID that implements the TPC model. To show that TPCs can improve existing electronic devices, this thesis describes applications of TPCs to implantable medical devices (IMDs), a challenging design space in which some battery-constrained devices completely lack protection against radio-based attacks. TPCs can provide security and privacy benefits to IMDs by, for instance, cryptographically authenticating other devices that want to communicate with the IMD before allowing the IMD to use any of its battery power. This thesis describes a simplified IMD that lacks its own radio, saving precious battery energy and therefore size. The simplified IMD instead depends on an RFID-scale TPC for all of its communication functions. TPCs are a natural area of exploration for future electronic design, given the parallel trends of energy harvesting and miniaturization. This work aims to establish and evaluate basic principles by which TPCs can operate

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Ekho: A Tool for Recording and Emulating Energy Harvesting Conditions

Harvested energy makes it possible to deploy sensing devices long-term with minimal required upkeep. However, as devices shrink, unpredictable power supplies make it difficult for system designers to anticipate the behavior of these devices. Ekho is tool that records and emulates energy harvesting conditions in order to enable accurate and repeatable testing of these sensing devices. Ekho uses the concept of I-V curves — curves that describe harvesting current in relation to supply voltage — in order to accurately represent harvesting conditions in a form that is independent of the sensing platform and the type of energy that is being harvested. This paper describes extensions to Ekho; it presents the design and an improved implementation, as well as preliminary testing and results. My role in this project has been to reimplement and to extend Ekho. This software was unmaintainable and considerably limited in its ability to emulate energy harvesting conditions. The first implementation of Ekho was a hardware design for an FPGA, which made use of specialized circuits. I refactored this code for a microcontroller, achieving even better performance than before: this new implementation can record harvesting conditions and can emulate changing I-V curves, and I have added back-end programs to ease processing and formatting of data. Initial results show that Ekho is able to replay I-V surfaces while readjusting to the harvesting conditions as frequently as once in 4.3μs. Ekho is able to emulate changing energy conditions, adapting both to changes in supply voltage and energy availability. Ekho can update the I-V curve, which the I-V controller holds in memory during emulation, as frequently as once per millisecond. These results show that Ekho is responsive to changes in the harvesting current and could be working properly

On the impact of mobility on battery-less RF energy harvesting system performance

The future of Internet of Things (IoT) envisions billions of sensors integrated with the physical environment. At the same time, recharging and replacing batteries on this infrastructure could result not only in high maintenance costs, but also large amounts of toxic waste due to the need to dispose of old batteries. Recently, battery-free sensor platforms have been developed that use supercapacitors as energy storage, promising maintenance-free and perpetual sensor operation. While prior work focused on supercapacitor characterization, modelling and supercapacitor-aware scheduling, the impact of mobility on capacitor charging and overall sensor application performance has been largely ignored. We show that supercapacitor size is critical for mobile system performance and that selecting an optimal value is not trivial: small capacitors charge quickly and enable the node to operate in low energy environments, but cannot support intensive tasks such as communication or reprogramming; increasing the capacitor size, on the other hand, enables the support for energy-intensive tasks, but may prevent the node from booting at all if the node navigates in a low energy area. The paper investigates this problem and proposes a hybrid storage solution that uses an adaptive learning algorithm to predict the amount of available ambient energy and dynamically switch between two capacitors depending on the environment. The evaluation based on extensive simulations and prototype measurements showed up to 40% and 80% improvement compared to a fixed-capacitor approach in terms of the amount of harvested energy and sensor coverage

Joint energy harvesting and communication analysis for perpetual wireless nanosensor networks in the terahertz band

Abstract—Wireless nanosensor networks (WNSNs) consist of nanosized communicating devices, which can detect and measure new types of events at the nanoscale. WNSNs are the enabling technology for unique applications such as intrabody drug delivery systems or surveillance networks for chemical attack prevention. One of the major bottlenecks in WNSNs is posed by the very limited energy that can be stored in a nanosensor mote in contrast to the energy that is required by the device to communicate. Recently, novel energy harvesting mechanisms have been proposed to replenish the energy stored in nanodevices. With these mechanisms, WNSNs can overcome their energy bottleneck and even have infinite lifetime (perpetual WNSNs), provided that the energy harvesting and consumption processes are jointly designed. In this paper, an energy model for self-powered nanosensor motes is developed, which successfully captures the correlation between the energy harvestin

Varying percentages of full uniform shading of a PV module in a controlled environment yields linear power reduction

Published ArticlePartial shading of a PV module has received much attention over the past few years, as it results in uneven cell power generation, compromising a PV system performance. Full uniform shading of a PV module has not received as much attention. This article correlates the percentage of full uniform shading of a given PV module within a controlled environment to its output power. The percentage of full uniform shading provided by shade nets was firstly determined. These shade nets are then used to cover a specific PV module (experimental system), while an identical PV module remains totally unshaded (control system). Increasing percentages of full uniform shading negatively affected the direct beam component in a linear way. Decreasing the light intensity falling on the PV model exhibited a linear increase in the percentage of output power reduction of the PV module. This is observed in that a shade net providing 36% of full uniform shading resulted in a 56% output power reduction, while a 63% full uniform shading net yielded 82% power reduction. These results hold a strong promise to improve current simulation modules that focus on determining the output power of a given PV array under specific environmental conditions or for specialised geographical locations

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about