Batteryless sensor nodes, powered solely by energy harvesting, are a promising alternative to battery-powered sensor nodes. However, energy harvesting rates being very low, unreliable, and time-varying, nodes cannot sustain a continuous operation, making them intermittently powered. As a result, these nodes incur unpredictable wakeup times due to continuously varying off-times. To perform tasks like distributed sensing, time synchronization, and communication for intermittently powered nodes, timely execution and robust coordination is vital. To achieve robust coordination, nodes must guarantee to be ON at a coordinated target time regardless of harvesting variations. To ensure robust coordination of on-times, we propose PAIL, a novel hardware-software approach where the hardware component enforces a constant off-time, with small variations. The software component dynamically corrects for those variations. We fabricated a PAIL sensor node and validated its ability to discover neighboring nodes. Using extensive simulations calibrated from experimental measurements, we observe that PAIL maintains nearly 99.3% coordination at steady state. In the context of pairwise communication, we show that leveraging PAIL coordination, nodes improve packet tail latency by 99%.

Batteryless sensor nodes powered solely by energy harvesting are a promising alternative to battery-powered sensor nodes. However, since the energy harvesting rate from these sources is often very low, unreliable, and time-varying, nodes cannot sustain a continuous operation, making them intermittently powered with unpredictable wakeup times. Moreover, energy harvesting rates differ significantly across deployment scenarios, influenced by environmental conditions, technology, and source availability. Current platforms are mainly designed to be best-effort with performance and reliability dictated by variations in incident input power. Therefore, application that demand critical end-to-end latency fails to achieve high Quality of Services (QOS) due to nodes not being able to compute and communicate in a timely and coordinated manner. Along with collecting, recording and distributing debug information, we propose a novel platform that enable robust coordination of on-times, timely computing and communication. Preliminary results on parts of our platform show nearly 99% coordination between pairs of sensor nodes and over 10x performance benefits for time critical inference tasks.

Batteryless systems offer promising platforms to support pervasive, near-sensor intelligence in a sustainable manner. These systems solely rely on ambient energy sources that often provide limited power. One common approach to designing batteryless systems is using intermittent execution---a node banks energy into a capacitive store until a threshold voltage is met and the digital components turn on and consume the banked energy until the energy is depleted and they die. The limited amount of available energy demands the development of application- and domain-specific accelerators to achieve energy efficiency and timeliness. Given the extremely close relationship between volatile state and intermittent behavior, performing actual system prototyping has been critical for demonstrating feasibility of intermittent systems. However, no prototyping platform exists for intermittent accelerators. This paper introduces BOBBER, the first implementation of an intermittent FPGA-based accelerator prototyping platform. We demonstrate BOBBER in the optimization and evaluation of a neural network accelerator powered solely by RF energy harvesting.

Batteryless energy-harvesting sensor nodes can operate indefinitely, but if the harvesting rate is too low, they must operate intermittently. Intermittent operation imposes various challenges upon the system. One of the least-studied is communication–if nodes are unpowered for long, unpredictable periods of time, how can they reliably communicate with each other? In prior work, we proposed the concept of lifecycle management protocols (LMPs) to mitigate this issue and enable wireless communication directly between intermittent sensor nodes using active radios. In this paper, we propose a design framework for a class of LMPs. We then provide analytical models for the delay and throughput of two-node communication using this framework. Finally, we implement this framework on hardware and validate our models in an experimental setting. To the best of our knowledge, this is the first design framework for, and implementation of, protocols for enabling and improving general-purpose communication between intermittent sensor nodes using active radios.

Nodes in batteryless sensor networks operate intermittently, making tasks such as node-to-node communication and coordinated computation extremely challenging. Adding to this challenge, a node typically has little control over its intermittency. Therefore, in this paper, we introduce a new class of protocols, which we call lifecycle management protocols (LMPs), to better control and manage the intermittency of batteryless nodes. These protocols may be designed and optimized for a particular task; here, we propose and evaluate a set of LMPs designed to enable direct communication between intermittent batteryless sensor nodes with active radios.

Batteryless sensing devices powered solely by ambient energy sources are expected to operate in an intermittent manner, since they do not have a predictable, or even continuous, energy supply. When such an intermittent system is powered off, it cannot keep track of time using conventional means. However, a continuous sense of time is critical for any system running real-time or time-sensitive applications. In this paper, we present HARC (Heterogeneous Array of Redundant Persistent Clocks), a novel solution to the problem of timekeeping for batteryless, intermittently-powered systems. HARC uses a heterogeneous, redundant array of capacitor-based persistent clocks that each decay in parallel, but at different rates, to provide variation-resilient high accuracy over a wide range of power off-times. We demonstrate the feasibility and effectiveness of HARC using experimental evaluations on a HARC prototype, and trace-based simulations of HARC-supported communication directly between two devices intermittently-powered by RF harvesting.