The EH Model: Analytical Exploration of Energy-Harvesting Architectures

Miguel, Joshua San; Ganesan, Karthik; Badr, Mario; Jerger, Natalie Enright

doi:10.1109/lca.2017.2777834

Cited by 18 publications

(17 citation statements)

References 10 publications

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“…The energy cost of a checkpoint is the product of the average number of bytes it contains d b and the energy cost of writing and reading a byte of data e b . As prior work [2], [3], we find that backup and restore costs are nearly perfectly linear in the number of bytes that needs to be read or written. Idle: ULP-systems use sleep modes, which are low-energy states where selected components are either power-gated or clock-gated, to save energy while idle.…”

Section: The Pes Modelsupporting

confidence: 62%

“…Our Periodic Energy-Harvesting Systems (PES) model enables IoT developers to select sustainable near-energy-neutral design points by faithfully modeling the energy consumption of computation and communication. In contrast, the state-of-theart EH-model [2], [3] only models computation and backup; backups have a high energy cost in communicating systems because the connection to the back-end system needs to be reestablished when power returns. Across our IoT applications, PES predicts energy consumption with an average error of 0.5% (maximally 1.4%) relative to our real-hardware baseline and simulator for energy-feasible and intermittent design points, respectively.…”

Section: Resume Thresholdmentioning

confidence: 99%

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Modeling Periodic Energy-Harvesting Computing Systems

Ghasemi

Jahre

2021

IEEE Comput. Arch. Lett.

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The Internet of Things (IoT) requires Ultra-Low Power (ULP) systems that communicate wirelessly and solely rely on harvested energy to scalably interact with the environment. This is challenging for IoT developers because (i) energy and performance are fundamentally intertwined -since capturing sensor samples and communicating more frequently increases energy consumption -and (ii) the performance versus energy trade-off typically needs to evaluated before ULP-platform selection -as the developer needs to be sure that a sufficiently performant system can be built before incurring the (substantial) effort of implementing the application on the ULP-platform. In this paper, we present the Periodic Energy-Harvesting Systems (PES) model which enables such trade-offs by faithfully modeling the energy impact of changing sampling and communication rates. Across our IoT applications, PES has an average energy prediction error of only 0.5%. In contrast, the average error of the state-of-the-art EH-model is 77.0%.

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Section: The Pes Modelsupporting

confidence: 62%

Section: Resume Thresholdmentioning

confidence: 99%

Modeling Periodic Energy-Harvesting Computing Systems

Ghasemi

Jahre

2021

IEEE Comput. Arch. Lett.

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“…Energy consumption evaluation requires precise measurements and a model of the platform. For ultra-low power systems, allowing intermittent execution, a variety of models has been proposed [22]- [24]. The EPIC modeling tool [25] supports temperature variation and clock drifts in power consumption estimation.…”

Section: Context and State Of The Artmentioning

confidence: 99%

Accurate Power Consumption Evaluation for Peripherals in Ultra Low-Power embedded systems

Berthou

Marquet

Risset

et al. 2020

2020 Global Internet of Things Summit (GIoTS)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…Nonetheless, equally important are the work before and after the modeling stage. Early on, analytical models like EH-Model [15] can be used to rapidly explore the design space. Tools like Ekho [3] and Shepherd [16] aid the designer throughout the design flow by providing a means for accurate power profiling (research and survey) and replaying the traces during modeling and/or hardware validation.…”

Section: Model-based Batteryless Eh-wsn Designmentioning

confidence: 99%

Energy-aware HW/SW Co-modeling of Batteryless Wireless Sensor Nodes

Wong

Sliper

Wang

et al. 2020

Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems

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Energy harvesting wireless sensor nodes are sensitive to spatial and temporal fluctuations in energy availability. This issue is especially prevalent in batteryless systems, where devices are directly connected to power sources with little or no buffering. The strong coupling of energy supply and demand introduces a new dimension to the problem of designing robust networked sensing systems. We propose a modeling framework for this class of batteryless systems with an emphasis on the interactions between energy and function. The tool models energy harvesters, power management circuitry, energy storage, microcontrollers, sensors, radio modules, environmental models, and is fully extensible. The microcontroller model is based on cycle-accurate instruction set simulators from Fused, with various peripheral extensions to enable board-level functionality, such as SPI, DMA, hardware multiplier etc. The tool enables virtual prototyping of self-powered wireless sensor nodes, but is especially useful for studying intermittent operation and developing application specific software, hardware, or combined solutions. The simulator is capable of executing real workloads under realistic conditions and this is demonstrated through a case study where the same compiled binary is executed on a virtual prototype and its corresponding physical wireless sensor system to yield matching digital traces and current profiles.

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The EH Model: Analytical Exploration of Energy-Harvesting Architectures

Cited by 18 publications

References 10 publications

Modeling Periodic Energy-Harvesting Computing Systems

Modeling Periodic Energy-Harvesting Computing Systems

Accurate Power Consumption Evaluation for Peripherals in Ultra Low-Power embedded systems

Energy-aware HW/SW Co-modeling of Batteryless Wireless Sensor Nodes

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