skip to main content
research-article
Public Access
Best Paper

A Reconfigurable Energy Storage Architecture for Energy-harvesting Devices

Published:19 March 2018Publication History
Skip Abstract Section

Abstract

Battery-free, energy-harvesting devices operate using energy collected exclusively from their environment. Energy-harvesting devices allow maintenance-free deployment in extreme environments, but requires a power system to provide the right amount of energy when an application needs it. Existing systems must provision energy capacity statically based on an application's peak demand which compromises efficiency and responsiveness when not at peak demand. This work presents Capybara: a co-designed hardware/software power system with dynamically reconfigurable energy storage capacity that meets varied application energy demand. The Capybara software interface allows programmers to specify the energy mode of an application task. Capybara's runtime system reconfigures Capybara's hardware energy capacity to match application demand. Capybara also allows a programmer to write reactive application tasks that pre-allocate a burst of energy that it can spend in response to an asynchronous (e.g., external) event. We instantiated Capybara's hardware design in two EH devices and implemented three reactive sensing applications using its software interface. Capybara improves event detection accuracy by 2x-4x over statically-provisioned energy capacity, maintains response latency within 1.5x of a continuously-powered baseline, and enables reactive applications that are intractable with existing power systems.

References

  1. Michael P. Andersen, Gabe Fierro, and David E. Culler. System design for a synergistic, low power mote/BLE embedded platform. In Information Processing in Sensor Networks (IPSN), 2016 15th ACM/IEEE International Conference on, pages 1--12. IEEE, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Anirudh Badam, Evangelia Skiani, Ranveer Chandra, Jon Dutra, Anthony Ferrese, Steve Hodges, Pan Hu, Julia Meinershagen, Thomas Moscibroda, and Bodhi Priyantha. Software defined batteries. pages 215--229. ACM Press, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Woongki Baek and Trishul M. Chilimbi. Green: a framework for supporting energy-conscious programming using controlled approximation. In ACM Sigplan Notices, volume 45, pages 198--209. ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Domenico Balsamo, Alex S Weddell, Anup Das, Alberto Rodriguez Arreola, Davide Brunelli, Bashir M Al-Hashimi, Geoff V Merrett, and Luca Benini. HibernusGoogle ScholarGoogle Scholar
  5. : a self-calibrating and adaptive system for transiently-powered embedded devices. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 35(12):1968--1980, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Domenico Balsamo, Alex S Weddell, Geoff V Merrett, Bashir M Al-Hashimi, Davide Brunelli, and Luca Benini. Hibernus: Sustaining computation during intermittent supply for energy-harvesting systems. IEEE Embedded Systems Letters, 7(1):15--18, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  7. Naveed Anwar Bhatti and Luca Mottola. HarvOS: efficient code instrumentation for transiently-powered embedded sensing. pages 209--219. ACM Press, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Anthony Canino and Yu David Liu. Proactive and adaptive energy-aware programming with mixed typechecking. pages 217--232. ACM Press, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Hari Cherupalli, Henry Duwe, Weidong Ye, Rakesh Kumar, and John Sartori. Determining Application-specific Peak Power and Energy Requirements for Ultra-low Power Processors. pages 3--16. ACM Press, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Michael Cohen, Haitao Steve Zhu, Emgin Ezgi Senem, and Yu David Liu. Energy types. In ACM SIGPLAN Notices, volume 47, pages 831--850. ACM, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Alexei Colin and Brandon Lucia. Chain: tasks and channels for reliable intermittent programs. In Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 514--530. ACM, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Andres Gomez, Lukas Sigrist, Thomas Schalch, Luca Benini, and Lothar Thiele. Efficient, long-term logging of rich data sensors using transient sensor nodes. ACM Trans. Embed. Comput. Syst., 17(1):4:1--4:23, September 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Josiah Hester, Sarah Lord, Ryan Halter, David Kotz, Jacob Sorber, Travis Peters, Tianlong Yun, Ronald Peterson, Joseph Skinner, Bhargav Golla, Kevin Storer, Steven Hearndon, and Kevin Freeman. Amulet: An Energy-Efficient, Multi-Application Wearable Platform. pages 216--229. ACM Press, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Josiah Hester, Lanny Sitanayah, and Jacob Sorber. Tragedy of the coulombs: Federating energy storage for tiny, intermittently-powered sensors. In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, pages 5--16. ACM, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Matthew Hicks. Clank: Architectural Support for Intermittent Computation. pages 228--240. ACM Press, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Henry Hoffmann, Stelios Sidiroglou, Michael Carbin, Sasa Misailovic, Anant Agarwal, and Martin Rinard. Dynamic knobs for responsive power-aware computing. In ACM SIGPLAN Notices, volume 46, pages 199--212. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Hrishikesh Jayakumar, Arnab Raha, and Vijay Raghunathan. Quickrecall: A low overhead hw/sw approach for enabling computations across power cycles in transiently powered computers. In VLSI Design and 2014 13th International Conference on Embedded Systems, 2014 27th International Conference on, pages 330--335. IEEE, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Xiaofan Jiang, Joseph Polastre, and David Culler. Perpetual environmentally powered sensor networks. In Proceedings of the 4th international symposium on Information processing in sensor networks, page 65. IEEE Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Philo Juang, Hidekazu Oki, Yong Wang, Margaret Martonosi, Li Shiuan Peh, and Daniel Rubenstein. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with zebranet. In ACM Sigplan Notices, volume 37, pages 96--107. ACM, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Melanie Kambadur and Martha A. Kim. NRG-loops: adjusting power from within applications. pages 206--215. ACM Press, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Aman Kansal, Scott Saponas, A.J. Bernheim Brush, Kathryn S. McKinley, Todd Mytkowicz, and Ryder Ziola. The latency, accuracy, and battery (LAB) abstraction: programmer productivity and energy efficiency for continuous mobile context sensing. pages 661--676. ACM Press, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Steve Kerrison and Kerstin Eder. Energy Modeling of Software for a Hardware Multithreaded Embedded Microprocessor. ACM Transactions on Embedded Computing Systems, 14(3):1--25, April 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Philip Levis, Sam Madden, Joseph Polastre, Robert Szewczyk, Kamin Whitehouse, Alec Woo, David Gay, Jason Hill, Matt Welsh, Eric Brewer, and others. TinyOS: An operating system for sensor networks. Ambient intelligence, 35:115--148, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  24. Brandon Lucia and Benjamin Ransford. A simpler, safer programming and execution model for intermittent systems. In ACM SIGPLAN Notices, volume 50, pages 575--585. ACM, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Kaisheng Ma, Yang Zheng, Shuangchen Li, Karthik Swaminathan, Xueqing Li, Yongpan Liu, Jack Sampson, Yuan Xie, and Vijaykrishnan Narayanan. Architecture exploration for ambient energy harvesting nonvolatile processors. In High Performance Computer Architecture (HPCA), 2015 IEEE 21st International Symposium on, pages 526--537. IEEE, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  26. Kiwan Maeng, Alexei Colin, and Brandon Lucia. Alpaca: Intermittent execution without checkpoints. In Proceedings of the 2017 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications. ACM, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Robert Margolies, Peter Kinget, Ioannis Kymissis, Gil Zussman, Maria Gorlatova, John Sarik, Gerald Stanje, Jianxun Zhu, Paul Miller, Marcin Szczodrak, Baradwaj Vigraham, and Luca Carloni. Energy-Harvesting Active Networked Tags (EnHANTs): Prototyping and Experimentation. ACM Transactions on Sensor Networks, 11(4):1--27, November 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Azalia Mirhoseini, Ebrahim M Songhori, and Farinaz Koushanfar. Idetic: A high-level synthesis approach for enabling long computations on transiently-powered asics. In Pervasive Computing and Communications (PerCom), 2013 IEEE International Conference on, pages 216--224. IEEE, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  29. Chulsung Park and Pai H. Chou. Ambimax: Autonomous energy harvesting platform for multi-supply wireless sensor nodes. In Sensor and Ad Hoc Communications and Networks, 2006. SECON'06. 2006 3rd Annual IEEE Communications Society on, volume 1, pages 168--177. IEEE, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  30. Chulsung Park, Jinfeng Liu, and Pai H. Chou. Eco: an ultra-compact low-power wireless sensor node for real-time motion monitoring. In Proceedings of the 4th international symposium on Information processing in sensor networks, page 54. IEEE Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Powercast Corporation. P2110B 915MHz RF Powerharvester Receiver. http://www.powercastco.com/products/powerharvester-receivers/, 2017.Google ScholarGoogle Scholar
  32. Vijay Raghunathan, Aman Kansal, Jason Hsu, Jonathan Friedman, and Mani Srivastava. Design considerations for solar energy harvesting wireless embedded systems. In Proceedings of the 4th international symposium on Information processing in sensor networks, page 64. IEEE Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Benjamin Ransford, Jacob Sorber, and Kevin Fu. Mementos: System support for long-running computation on rfid-scale devices. Acm Sigplan Notices, 47(4):159--170, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Alanson P Sample, Daniel J Yeager, Pauline S Powledge, Alexander V Mamishev, and Joshua R Smith. Design of an rfid-based battery-free programmable sensing platform. IEEE Transactions on Instrumentation and Measurement, 57(11):2608--2615, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  35. Adrian Sampson, Werner Dietl, Emily Fortuna, Danushen Gnanapragasam, Luis Ceze, and Dan Grossman. EnerJ: Approximate data types for safe and general low-power computation. In ACM SIGPLAN Notices, volume 46, pages 164--174. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Faisal Karim Shaikh and Sherali Zeadally. Energy harvesting in wireless sensor networks: A comprehensive review. Renewable and Sustainable Energy Reviews, 55:1041--1054, March 2016.Google ScholarGoogle ScholarCross RefCross Ref
  37. Jacob Sorber, Alexander Kostadinov, Matthew Garber, Matthew Brennan, Mark D Corner, and Emery D Berger. Eon: a language and runtime system for perpetual systems. In Proceedings of the 5th international conference on Embedded networked sensor systems, pages 161--174. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Phillip Stanley-Marbell and Diana Marculescu. An 0.9x1.2, low power, energy-harvesting system with custom multi-channel communication interface. In Proceedings of the conference on Design, automation and test in Europe, pages 15--20. EDA Consortium, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Joel Van Der Woude and Matthew Hicks. Intermittent computation without hardware support or programmer intervention. In Proceedings of OSDI'16: 12th USENIX Symposium on Operating Systems Design and Implementation, page 17, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Lohit Yerva, Brad Campbell, Apoorva Bansal, Thomas Schmid, and Prabal Dutta. Grafting energy-harvesting leaves onto the sensornet tree. In Proceedings of the 11th international conference on Information Processing in Sensor Networks, pages 197--208. ACM, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Zac Manchester. KickSat. http://zacinaction.github.io/kicksat/, 2015.Google ScholarGoogle Scholar
  42. Hong Zhang, Jeremy Gummeson, Benjamin Ransford, and Kevin Fu. Moo: A batteryless computational rfid and sensing platform. Department of Computer Science, University of Massachusetts Amherst., Tech. Rep, 2011.Google ScholarGoogle Scholar
  43. Ting Zhu, Yu Gu, Tian He, and Zhi-Li Zhang. eShare: a capacitor-driven energy storage and sharing network for long-term operation. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, pages 239--252. ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A Reconfigurable Energy Storage Architecture for Energy-harvesting Devices

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM SIGPLAN Notices
        ACM SIGPLAN Notices  Volume 53, Issue 2
        ASPLOS '18
        February 2018
        809 pages
        ISSN:0362-1340
        EISSN:1558-1160
        DOI:10.1145/3296957
        Issue’s Table of Contents
        • cover image ACM Conferences
          ASPLOS '18: Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems
          March 2018
          827 pages
          ISBN:9781450349116
          DOI:10.1145/3173162

        Copyright © 2018 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 March 2018

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader
      About Cookies On This Site

      We use cookies to ensure that we give you the best experience on our website.

      Learn more

      Got it!