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. CCS Concepts. • Computer systems organization → Embedded software; • Hardware → Emerging architectures; Impact on the environment; • Software and its engineering → Runtime environments; Source code generation.
RF-based wireless power transfer networks (WPTNs) are deployed to transfer power to embedded devices over the air via radio frequency waves. Up until now, a considerable amount of effort has been devoted by researchers to design WPTNs that maximize several objectives such as harvested power, energy outage and charging delay. However, inherent security and safety issues are generally overlooked and these need to be solved if WPTNs are to be become widespread. This article focuses on safety and security problems related WPTNs and highlight their cruciality in terms of efficient and dependable operation of RF-based WPTNs. We provide a overview of new research opportunities in this emerging domain.
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.
Energy-neutral Internet of Things requires freeing embedded devices from batteries and powering them from ambient energy. Ambient energy is, however, unpredictable and can only power a device intermittently. Therefore, the paradigm of intermittent execution is to save the program state into non-volatile memory frequently to preserve the execution progress. In task-based intermittent programming, the state is saved at task transition. Tasks are fixed at compile time and agnostic to energy conditions. Thus, the state may be saved either more often than necessary or not often enough for the program to progress and terminate. To address these challenges, we propose Coala, an adaptive and efficient task-based execution model. Coala progresses on a multi-task scale when energy permits and preserves the computation progress on a sub-task scale if necessary. Coala's specialized memory virtualization mechanism ensures that power failures do not leave the program state in non-volatile memory inconsistent. Our evaluation on a real energy-harvesting platform not only shows that Coala reduces runtime by up to 54% as compared to a state-of-the-art system, but also it is able to progress where static systems fail. CCS Concepts: • Hardware → Power and energy; • Software and its engineering → Embedded software; Virtual memory;
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