More Web Proxy on the site http://driver.im/

research-article

Operating Energy-Neutral Real-Time Systems

Authors:

Peter Wägemann,

Tobias Distler,

Phillip Raffeck,

Wolfgang SchröDer-PreikschatAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 17, Issue 1

Article No.: 11, Pages 1 - 25

https://doi.org/10.1145/3078631

Published: 29 August 2017 Publication History

Abstract

Energy-neutral real-time systems harvest the entire energy they use from their environment. In such systems, energy must be treated as an equally important resource as time, which creates the need to solve a number of problems that so far have not been addressed by traditional real-time systems. In particular, this includes the scheduling of tasks with both time and energy constraints, the monitoring of energy budgets, as well as the survival of blackout periods during which not enough energy is available to keep the system fully operational.

In this article, we address these issues presenting EnOS, an operating-system kernel for energy-neutral real-time systems. EnOS considers mixed time criticality levels for different energy criticality modes, which enables a decoupling of time and energy constraints when one is considered less critical than the other. When switching the energy criticality mode, the system also changes the set of executed tasks and is therefore able to dynamically adapt its energy consumption depending on external conditions. By keeping track of the energy budget available, EnOS ensures that in case of a blackout the system state is safely stored to persistent memory, allowing operations to resume at a later point when enough energy is harvested again.

References

[1]

M. Bambagini, M. Bertogna, and G. Buttazzo. 2014. On the effectiveness of energy-aware real-time scheduling algorithms on single-core platforms. In Proceedings of the 20th International Conference on Emerging Technology and Factory Automation. 1--8.

[2]

S. Baruah, V. Bonifaci, G. D’Angelo, H. Li, A. Marchetti-Spaccamela, N. Megow, and L. Stougie. 2012. Scheduling real-time mixed-criticality jobs. IEEE Trans. Comput. 61, 8 (2012), 1140--1152.

Digital Library

[3]

I. Bate, A. Burns, and R. I. Davis. 2015. A bailout protocol for mixed criticality systems. In Proceedings of the 27th Euromicro Conference on Real-Time Systems. 259--268.

Digital Library

[4]

E. Bini and G. C. Buttazzo. 2005. Measuring the performance of schedulability tests. Real-Time Syst. 30 (2005), 129--154.

Digital Library

[5]

E. Bini, G. Buttazzo, and G. Lipari. 2005. Speed modulation in energy-aware real-time systems. In Proceedings of the 17th Euromicro Conference on Real-Time Systems. 3--10.

Digital Library

[6]

B. Buchli, D. Aschwanden, and J. Beutel. 2013. Battery state-of-charge approximation for energy harvesting embedded systems. In Proceedings of the 10th European Conference on Wireless Sensor Networks. 179--196.

Digital Library

[7]

B. Buchli, P. Kumar, and L. Thiele. 2015. Optimal power management with guaranteed minimum energy utilization for solar energy harvesting systems. In Proceedings of the 11th International Conference on Distributed Computing in Sensor Systems. 147--158.

Digital Library

[8]

B. Buchli, F. Sutton, J. Beutel, and L. Thiele. 2014. Dynamic power management for long-term energy neutral operation of solar energy harvesting systems. In Proceedings of the 12th Conference on Embedded Network Sensor Systems. 31--45.

Digital Library

[9]

A. Burns. 2014. System mode changes -- general and criticality-based. In Proceedings of the 2nd Workshop on Mixed Criticality Systems. 3--8.

[10]

A. Burns and R. I. Davis. 2015. Mixed Criticality Systems—A Review. 6th ed. Department of Computer Science, University of York, York, UK.

[11]

J. Constine. 2014. Facebook Will Deliver Internet Via Drones With “Connectivity Lab” Project Powered By Acqhires From Ascenta. (2014). Retrieved from http://techcrunch.com/2014/03/27/facebook-drones/.

[12]

Eaton. 2016. HV Supercapacitors—Cylindrical cells.

[13]

Fujitsu Semiconductor. 2013. FRAM MB85RC256V.

[14]

Google Inc. 2016. Project Loon. (2016). Retrieved from https://www.google.com/loon/.

[15]

C. Gu, N. Guan, Q. Deng, and W. Yi. 2013. Improving OCBP-based scheduling for mixed-criticality sporadic task systems. In Proceedings of the 19th International Conference on Embedded and Real-Time Computing Systems and Applications. 247--256.

[16]

T. Hönig, H. Janker, C. Eibel, O. Mihelic, R. Kapitza, and W. Schröder-Preikschat. 2014. Proactive energy-aware programming with PEEK. In Proceedings of the Conference on Timely Results in Operating Systems. 1--14.

[17]

Intersil. 2016. ISL85412—Synchronous Buck Regulator.

[18]

R. Jayaseelan, T. Mitra, and X. Li. 2006. Estimating the worst-case energy consumption of embedded software. In Proceedings of the 12th Real-Time and Embedded Technology and Applications Symposium. 81--90.

Digital Library

[19]

A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava. 2007. Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems 6, 4 (2007).

Digital Library

[20]

J. P. Lehoczky, L. Sha, and J. K. Strosnider. 1987. Enhanced aperiodic responsiveness in a hard-real-time environment. In Proceedings of the 8th Real-Time Systems Symposium. 261--270.

[21]

B. Lucia and B. Ransford. 2015. A simpler, safer programming and execution model for intermittent systems. In Proceedings of the 36th Conference on Programming Language Design and Implementation. 575--585.

Digital Library

[22]

M. H. Mahmud, R. Saha, and S. Islam. 2013. Smart walking stick -- An electronic approach to assist visually disabled persons. Int. J. Sci. Eng. Res. 4, 10 (2013).

[23]

J. Pallister, S. Kerrison, J. Morse, and K. Eder. 2015. Data dependent energy modelling: A worst case perspective. Comput. Res. Repos. arXiv (2015).

[24]

P. Puschner and A. Schedl. 1997. Computing maximum task execution times: A graph-based approach. Real-Time Systems 13 (1997), 67--91.

Digital Library

[25]

J. Real and A. Crespo. 2004. Mode change protocols for real-time systems: A survey and a new proposal. Real-Time Systems 26, 2 (2004), 161--197.

Digital Library

[26]

C. Renner and V. Turau. 2012. State-of-charge assessment for supercap-powered sensor nodes: Keep it simple stupid!. In Proceedings of the 9th International Conference on Networked Sensing.

[27]

K. Ryokai, P. Su, E. Kim, and B. Rollins. 2014. EnergyBugs: Energy harvesting wearables for children. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1039--1048.

Digital Library

[28]

M. Sand, S. Potyra, and V. Sieh. 2009. Deterministic high-speed simulation of complex systems including fault-injection. In Proceedings of the 39th Conference on Dependable Systems and Networks. 211--216.

[29]

V. Sieh, R. Burlacu, T. Hönig, H. Janker, P. Raffeck, P. Wägemann, and W. Schröder-Preikschat. 2017. An end-to-end toolchain: From automated cost modeling to static WCET and WCEC analysis. In Proceedings of the 20th International Symposium on Real-Time Computing. 1--10.

[30]

P. Ulbrich, R. Kapitza, C. Harkort, R. Schmid, and W. Schröder-Preikschat. 2011. I4Copter: An adaptable and modular quadrotor platform. In Proceedings of the 26th ACM Symposium on Applied Computing (SAC’11). 380--396.

[31]

S. Vestal. 2007. Preemptive scheduling of multi-criticality systems with varying degrees of execution time assurance. In Proceedings of the 28th Real-Time Systems Symposium. 239--243.

Digital Library

[32]

M. Völp, M. Hähnel, and A. Lackorzynski. 2014. Has energy surpassed timeliness? Scheduling energy-constrained mixed-criticality systems. In Proceedings of the 20th Real-Time and Embedded Technology and Applications Symposium. 275--284.

[33]

P. Wägemann, T. Distler, T. Hönig, H. Janker, R. Kapitza, and W. Schröder-Preikschat. 2015. Worst-case energy consumption analysis for energy-constrained embedded systems. In Proceedings of the 27th Euromicro Conference on Real-Time Systems. 105--114.

[34]

P. Wägemann, T. Distler, H. Janker, P. Raffeck, and V. Sieh. 2016. A kernel for energy-neutral real-time systems with mixed criticalities. In Proceedings of the 22nd Real-Time and Embedded Technology and Applications Symposium. 25--36.

[35]

I. Wenzel, R. Kirner, B. Rieder, and P. Puschner. 2008. Measurement-based timing analysis. Leverag. Appl. Formal Meth., Verificat. Validat. 17 (2008), 430--444.

[36]

R. Wilhelm et al. 2008. The worst-case execution-time problem—Overview of methods and survey of tools. ACM Trans. Embed. Comput. Syst. 7, 3 (2008), 1--53.

Digital Library

[37]

H. Zeng, X. Fan, C. Ellis, A. Lebeck, and A. Vahdat. 2002. ECOSystem: Managing energy as a first class operating system resource. In Proceedings of the 10th Conference on Architectural Support for Programming Languages and Operating Systems. 123--132.

Digital Library

[38]

T. Zhu, Z. Zhong, Y. Gu, T. He, and Z.-L. Zhang. 2009. Leakage-aware energy synchronization for wireless sensor networks. In Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services. 319--332.

Digital Library

[39]

Y. Zhu and F. Mueller. 2004. Feedback EDF scheduling exploiting dynamic voltage scaling. In Proceedings of the 10th Real-Time and Embedded Technology and Applications Symposium. 84--93.

[40]

M. Zwerg, A. Baumann, R. Kuhn, M. Arnold, R. Nerlich, M. Herzog, R. Ledwa, C. Sichert, V. Rzehak, P. Thanigai, and B. O. Eversmann. 2011. An 82A/MHz microcontroller with embedded FeRAM for energy-harvesting applications. In Proceedings of the International Solid-State Circuits Conference. 334--336.

Cited By

Böhm HDistler TWägemann P(2024)TinyBFT: Byzantine Fault-Tolerant Replication for Highly Resource-Constrained Embedded Systems2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS)10.1109/RTAS61025.2024.00026(225-238)Online publication date: 13-May-2024
https://doi.org/10.1109/RTAS61025.2024.00026
Vogelgesang KRaffeck PWägemann PHerfet TSchröder-Preikschat W(2024)WIP: Towards a Transactional Network Stack for Power-Failure Resilience2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454781(803-806)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454781
Wägemann P(2022)Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical SystemsErnst Denert Award for Software Engineering 202010.1007/978-3-030-83128-8_11(227-247)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-83128-8_11
Show More Cited By

Index Terms

Operating Energy-Neutral Real-Time Systems
1. Computer systems organization
  1. Real-time systems
    1. Real-time operating systems

Recommendations

Prediction free energy neutral power management for energy harvesting wireless sensor nodes

Current power management mechanisms for energy harvesting wireless sensors typically rely on predicted information about the amount of energy that can be harvested in the future. However, such mechanisms suffer from inevitable prediction errors, which ...
Ultra low power asynchronous MAC protocol using wake-up radio for energy neutral WSN
ENSSys '13: Proceedings of the 1st International Workshop on Energy Neutral Sensing Systems

To extend the system lifetime of WSN, energy harvesting techniques have been considered as potential solutions for long-term operations. Instead of minimizing the consumed energy as for the case of battery-powered systems, the harvesting node is adapted ...
Joint Energy Management for Distributed Energy Harvesting Systems
SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems

Employing energy harvesting to power the Internet of Things supports their long-term, self-sustainable, and maintenance-free operation. These energy harvesting systems have an energy management subsystem to orchestrate the flow of energy and optimize ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 17, Issue 1

Special Issue on Autonomous Battery-Free Sensing and Communication, Special Issue on ESWEEK 2016 and Regular Papers

January 2018

630 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/3136518

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 29 August 2017

Accepted: 01 April 2017

Revised: 01 January 2017

Received: 01 June 2016

Published in TECS Volume 17, Issue 1

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
308
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)4

Reflects downloads up to 28 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Böhm HDistler TWägemann P(2024)TinyBFT: Byzantine Fault-Tolerant Replication for Highly Resource-Constrained Embedded Systems2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS)10.1109/RTAS61025.2024.00026(225-238)Online publication date: 13-May-2024
https://doi.org/10.1109/RTAS61025.2024.00026
Vogelgesang KRaffeck PWägemann PHerfet TSchröder-Preikschat W(2024)WIP: Towards a Transactional Network Stack for Power-Failure Resilience2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454781(803-806)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454781
Wägemann P(2022)Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical SystemsErnst Denert Award for Software Engineering 202010.1007/978-3-030-83128-8_11(227-247)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-83128-8_11
García Baquerizo JSuárez AMacias ESalas E(2019)Hardware Mechanism for Energy Saving in WiFi Access PointsSensors10.3390/s1921474519:21(4745)Online publication date: 1-Nov-2019
https://doi.org/10.3390/s19214745
Eichler CWägemann PSchröder-Preikschat WZimmerling M(2019)GENEEProceedings of the 2nd Workshop on Benchmarking Cyber-Physical Systems and Internet of Things10.1145/3312480.3313170(1-6)Online publication date: 15-Apr-2019
https://dl.acm.org/doi/10.1145/3312480.3313170

View Options

Login options

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

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents