Efficient State Retention for Transiently-powered Embedded Sensing

We present state retention techniques to support embedded sensing applications on 32-bit microcontrollers whose energy provisioning is assisted through ambient harvesting or wireless energy transfer. As energy availability is likely erratic in these settings, applications may be unpredictably interrupted. To behave dependably, applications should resume from where they left as soon as energy is newly available. We investigate the fundamental building block necessary to this end, and conceive three mechanisms to checkpoint and restore a device's state on stable storage quickly and in an energy-efficient manner. The problem is unique in many regards; for example, because of the distinctive performance vs. energy trade-offs of modern 32-bit microcontrollers and the peculiar characteristics of current flash chips. Our results, obtained from real experiments using two different platforms, crucially indicate that there is no ``one-size-fits-all'' solution. The performance depends on factors such as the amount of data to handle, how in memory the data is laid out, as well as an application's read/write patterns

HarvOS: Efficient code instrumentation for transiently-powered embedded sensing

We present code instrumentation strategies to allow transiently-powered embedded sensing devices efficiently checkpoint the system's state before energy is exhausted. Our solution, called HarvOS, operates at compile-time with limited developer intervention based on the control-flow graph of a program, while adapting to varying levels of remaining energy and possible program executions at run-time. In addition, the underlying design rationale allows the system to spare the energy-intensive probing of the energy buffer whenever possible. Compared to existing approaches, our evaluation indicates that HarvOS allows transiently-powered devices to complete a given workload with 68% fewer checkpoints, on average. Moreover, our performance in the number of required checkpoints rests only 19% far from that of an "oracle" that represents an ideal solution, yet unfeasible in practice, that knows exactly the last point in time when to checkpoint

DiCA: A Hardware-Software Co-Design for Differential Checkpointing in Intermittently Powered Devices

Intermittently powered devices rely on opportunistic energy-harvesting to function, leading to recurrent power interruptions. This paper introduces DiCA, a proposal for a hardware/software co-design to create differential check-points in intermittent devices. DiCA leverages an affordable hardware module that simplifies the check-pointing process, reducing the check-point generation time and energy consumption. This hardware module continuously monitors volatile memory, efficiently tracking modifications and determining optimal check-point times. To minimize energy waste, the module dynamically estimates the energy required to create and store the check-point based on tracked memory modifications, triggering the check-pointing routine optimally via a nonmaskable interrupt. Experimental results show the cost-effectiveness and energy efficiency of DiCA, enabling extended application activity cycles in intermittently powered embedded devices.Comment: 8 pages and 7 figures. To be published at IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 202

Energy-Efficient System Architectures for Intermittently-Powered IoT Devices

Various industry forecasts project that, by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), helping to engineer new solutions to societal-scale problems such as healthcare, energy conservation, transportation, etc. Most of these devices will be wireless due to the expense, inconvenience, or in some cases, the sheer infeasibility of wiring them. With no cord for power and limited space for a battery, powering these devices for operating in a set-and-forget mode (i.e., achieve several months to possibly years of unattended operation) becomes a daunting challenge. Environmental energy harvesting (where the system powers itself using energy that it scavenges from its operating environment) has been shown to be a promising and viable option for powering these IoT devices. However, ambient energy sources (such as vibration, wind, RF signals) are often minuscule, unreliable, and intermittent in nature, which can lead to frequent intervals of power loss. Performing computations reliably in the face of such power supply interruptions is challenging

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

Hibernus++: a self-calibrating and adaptive system for transiently-powered embedded devices

Energy harvesters are being used to power autonomous systems, but their output power is variable and intermittent. To sustain computation, these systems integrate batteries or supercapacitors to smooth out rapid changes in harvester output. Energy storage devices require time for charging and increase the size, mass and cost of systems. The field of transient computing moves away from this approach, by powering the system directly from the harvester output. To prevent an application from having to restart computation after a power outage, approaches such as Hibernus allow these systems to hibernate when supply failure is imminent. When the supply reaches the operating threshold, the last saved state is restored and the operation is continued from the point it was interrupted. This work proposes Hibernus++ to intelligently adapt the hibernate and restore thresholds in response to source dynamics and system load properties. Specifically, capabilities are built into the system to autonomously characterize the hardware platform and its performance during hibernation in order to set the hibernation threshold at a point which minimizes wasted energy and maximizes computation time. Similarly, the system auto-calibrates the restore threshold depending on the balance of energy supply and consumption in order to maximize computation time. Hibernus++ is validated both theoretically and experimentally on microcontroller hardware using both synthesized and real energy harvesters. Results show that Hibernus++ provides an average 16% reduction in energy consumption and an improvement of 17% in application execution time over stateof- the-art approaches

MPU-based incremental checkpointing for transiently-powered systems

International audienc

To checkpoint or not to checkpoint : that is the question

One of the major shortcomings in IoT/sensor networks is the finite energy supply available for computation and communication. To circumvent this issue, energy harvesting has been proposed to enable embedded devices to mitigate their dependency on traditional battery-driven power source. However, energy supply due to energy harvesting often varies, leading to nodes crashing due to energy exhaustion, with application(s) losing their state. Efficient state checkpointing in non-volatile memory (NVM) has been pro- posed to enable forward progress, albeit at the expense of significant overhead (viz., energy and time). In this paper, we show that, for a certain class of applications, state check- pointing may adversely affect the performance of the applications. This is different to checkpointing in traditional distributed system where network topology is generally assumed to be stable