Intermittently operating embedded computing platforms powered by energy harvesting require software frameworks to protect from errors caused by Write After Read (WAR) dependencies. A powerful method of code protection for systems with non-volatile main memory utilizes compiler analysis to insert a checkpoint inside each WAR violation in the code. However, such software frameworks are oblivious to the code structure - -and therefore, inefficient - -when many consecutive WAR violations exist. Our insight is that by transforming the input code, i.e., moving individual write operations from unique WARs close to each other, we can significantly reduce the number of checkpoints. This idea is the foundation for WARio: a set of compiler transformations for efficient code generation for intermittent computing. WARio, on average, reduces checkpoint overhead by 58%, and up to 88%, compared to the state of the art across various benchmarks.

Building and programming tiny battery-free energy harvesting embedded computer systems is hard for the average maker because of the lack of tools, hard to comprehend programming models, and frequent power failures. With the high ecologic cost of equipping the next trillion embedded devices with batteries, it is critical to equip the makers, hobbyists, and novice embedded systems programmers with easy-To-use tools supporting battery-free energy harvesting application development. This way, makers can create untethered embedded systems that are not plugged into the wall, the desktop, or even a battery, providing numerous new applications and allowing for a more sustainable vision of ubiquitous computing. In this paper, we present BFree, a system that makes it possible for makers, hobbyists, and novice embedded programmers to develop battery-free applications using Python programming language and widely available hobbyist maker platforms. BFree provides energy harvesting hardware and a power failure resilient version of Python, with durable libraries that enable common coding practice and off the shelf sensors. We develop demonstration applications, benchmark BFree against battery-powered approaches, and evaluate our system in a user study. This work enables makers to engage with a future of ubiquitous computing that is useful, long-Term, and environmentally responsible.

We present ENGAGE, the first battery-free, personal mobile gaming device powered by energy harvested from the gamer actions and sunlight. Our design implements a power failure resilient Nintendo Game Boy emulator that can run off-the-shelf classic Game Boy games like Tetris or Super Mario Land. This emulator is capable of intermittent operation by tracking memory usage, avoiding the need for always checkpointing all volatile memory, and decouples the game loop from user interface mechanics allowing for restoration after power failure. We build custom hardware that harvests energy from gamer button presses and sunlight, and leverages a mixed volatility memory architecture for efficient intermittent emulation of game binaries. Beyond a fun toy, our design represents the first battery-free system design for continuous user attention despite frequent power failures caused by intermittent energy harvesting. We tackle key challenges in intermittent computing for interaction including seamless displays and dynamic incentive-based gameplay for energy harvesting. This work provides a reference implementation and framework for a future of battery-free mobile gaming in a more sustainable Internet of Things.

Energy-harvesting devices have enabled Internet of Things applications that were impossible before. One core challenge of batteryless sensors that operate intermittently is reliable timekeeping. State-of-the-art low-power real-time clocks suffer from long start-up times (order of seconds) and have low timekeeping granularity (tens of milliseconds at best), often not matching timing requirements of devices that experience numerous power outages per second. Our key insight is that time can be inferred by measuring alternative physical phenomena, like the discharge of a simple RC circuit, and that timekeeping energy cost and accuracy can be modulated depending on the run-time requirements. We achieve these goals with a multi-tier timekeeping architecture, named Cascaded Hierarchical Remanence Timekeeper (CHRT), featuring an array of different RC circuits to be used for dynamic timekeeping requirements. The CHRT and its accompanying software interface are embedded into a fresh batteryless wireless sensing platform, called Botoks, capable of tracking time across power failures. Low start-up time (max 5 ms), high resolution (up to 1 ms) and run-time reconfigurability are the key features of our timekeeping platform. We developed two time-sensitive batteryless applications to demonstrate the approach: a bicycle analytics tool-where the CHRT is used to track time between revolutions of a bicycle wheel, and wireless communication-where the CHRT enables radio synchronization between two intermittently-powered sensors.

Tiny energy harvesting sensors that operate intermittently, without batteries, have become an increasingly appealing way to gather data in hard to reach places at low cost. Frequent power failures make forward progress, data preservation and consistency, and timely operation challenging. Unfortunately, state-of-the-art systems ask the programmer to solve these challenges, and have high memory overhead, lack critical programming features like pointers and recursion, and are only dimly aware of the passing of time and its effect on application quality. We present Time-sensitive Intermittent Computing System (TICS), a new platform for intermittent computing, which provides simple programming abstractions for handling the passing of time through intermittent failures, and uses this to make decisions about when data can be used or thrown away. Moreover, TICS provides predictable checkpoint sizes by keeping checkpoint and restore times small and reduces the cognitive burden of rewriting embedded code for intermittency without limiting expressibility or language functionality, enabling numerous existing embedded applications to run intermittently.

Batteryless sensor nodes compute, sense, and communicate using only energy harvested from the ambient. These devices promise long maintenance free operation in hard to deploy scenarios, making them an attractive alternative to battery-powered wireless sensor networks. However, complications from frequent power failures due to unpredictable ambient energy stand in the way of robust network operation. Unlike continuously-powered systems, intermittently-powered batteryless nodes lose their time upon each reboot, along with all volatile memory, making synchronization and coordination difficult. In this paper, we consider the case where each batteryless sensor is equipped with a hourglass capacitor to estimate the elapsed time between power failures. Contrary to prior work that focused on providing a continuous notion of time for a single batteryless sensor, we consider a network of batteryless sensors and explore how to provide a network-wide, continuous, and synchronous notion of time. First, we build a mathematical model that represents the estimated time between power failures by using hourglass capacitors. This allowed us to simulate the local (and continuous) time of a single batteryless node. Second, we show through simulations the effect of hourglass capacitors and in turn the performance degradation of the state of the art synchronization protocol in wireless sensor networks in a network of batteryless devices.

Energy harvesting and battery-free sensing devices show great promise for revolutionizing computing in the home, in the wild, and on the body. The promise of cheap, dense, and ubiquitous sensing technology brings new applications for the Internet of Things. However, the future programming model is blurry and complex. With a potential for trillions of devices, and thousands of devices per person on earth, programming languages and associated operating systems must be usable, flexible, and resource efficient. Because of the thousands of applications and fine grained differences in requirements, multi-tenancy may be a part of the solution to solving this programming model crisis. This paper explores the energy and resources costs, feasibility, and motivation for multi-tenancy on these tiniest of computing devices-namely the difficulties in scheduling tasks fairly, efficiently, and simply. Because of intermittent power, resources and energy must be mostly devoted towards user tasks, we implement a rudimentary operating system with low overhead to conduct experiments and test time-sharing and scheduling protocols. We close with a discussion on challenges to implementing a multi-tenant run-time on battery-free tags, and proposals for future work.

Tiny energy harvesting battery-free devices promise maintenance free operation for decades, providing swarm scale intelligence in applications from healthcare to building monitoring. These devices operate intermittently because of unpredictable, dynamic energy harvesting environments, failing when energy is scarce. Despite this dynamic operation, current programming models are static; they ignore the event-driven and time-sensitive nature of sensing applications, focusing only on preserving forward progress while maintaining performance. This paper proposes InK; the first reactive kernel that provides a novel way to program these tiny energy harvesting devices that focuses on their main application of event-driven sensing. InK brings an event-driven paradigm shift for batteryless applications, introducing building blocks and abstractions that enable reacting to changes in available energy and variations in sensing data, alongside task scheduling, while maintaining a consistent memory and sense of time. We implemented several event-driven applications for InK, conducted a user study, and benchmarked InK against the state-of-the-art; InK provides up to 14 times more responsiveness and was easier to use. We show that InK enables never before seen batteryless applications, and facilitates more sophisticated batteryless programs.