Poster abstract: The energy harvesting mode abstraction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a new abstraction for understanding energy harvesting behaviors in the wild, especially how these behaviors impact energy constrained and battery-free sensors. The Energy Harvesting Mode abstraction explores ways to make sense of energy harvesting behaviors. We take known energy harvesting datasets, and create a few of our own, then classify energy harvesting behavior into modes. Modes are periodic or repeated elements caused by systematic or fundamental attributes of the energy harvesting environment. We show the existence of these Energy Harvesting Modes using real world data and IV surfaces created with the Ekho emulator. We discuss the impacts and usage of this powerful abstraction, including enabling adaptation, test case generation, and eciency analysis for energy harvesting and intermittently powered sensing devices.

Original languageEnglish (US)
Title of host publicationSenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery, Inc
Pages418-419
Number of pages2
ISBN (Electronic)9781450359528
DOIs
StatePublished - Nov 4 2018
Event16th ACM Conference on Embedded Networked Sensor Systems, SENSYS 2018 - Shenzhen, China
Duration: Nov 4 2018Nov 7 2018

Publication series

NameSenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems

Conference

Conference16th ACM Conference on Embedded Networked Sensor Systems, SENSYS 2018
CountryChina
CityShenzhen
Period11/4/1811/7/18

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Keywords

  • Batteryless
  • Energy harvesting
  • IV surface

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

Cite this

Bakar, A., & Hester, J. D. (2018). Poster abstract: The energy harvesting mode abstraction. In SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems (pp. 418-419). (SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3274783.3275212