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

research-article

Reducing charge redistribution loss for supercapacitor-operated energy harvesting wireless sensor nodes

Authors:

Ying ZhangAuthors Info & Claims

ENSsys '14: Proceedings of the 2nd International Workshop on Energy Neutral Sensing Systems

Pages 31 - 36

https://doi.org/10.1145/2675683.2675691

Published: 06 November 2014 Publication History

Abstract

With increasing demand of long term applications, supercapacitors have been widely chosen as energy storage devices for energy harvesting aware wireless sensor networks( WSNs) due to their long charging-discharging life cycles. However, few studies have focused on charge redistribution effect of supercapacitors in WSNs. In this paper, we investigate charge redistribution of supercapacitor and explore how it affects long term energy neutral operation (ENO). The Variable Leakage Resistance (VLR) model is used to analyze the charge redistribution effect. Our results indicate that charge redistribution may cause considerable amount of extra energy loss in long term ENO. A practical algorithm to minimize charge redistribution loss during energy neutral operation is proposed. The algorithm is computationally lightweight and can be incorporated into the state-of-the-art duty cycling power management strategies in WSNs. The proposed algorithm is proved to be effective in keeping the main branch and the delayed branch balanced and thus lowering energy dissipation from charge redistribution.

References

[1]

Atmel. Atmega 128/128L datasheet. www.atmel.com, 2011.

[2]

W. Dargie. Dynamic power management in wireless sensor networks: State-of-the-art. Sensors Journal, IEEE, 12(5):1518--1528, 2012.

[3]

M. Gorlatova, A. Wallwater, and G. Zussman. Networking low-power energy harvesting devices: Measurements and algorithms. Mobile Computing, IEEE Transactions on, 12(9):1853--1865, 2013.

Digital Library

[4]

X. Jiang, J. Polastre, and D. Culler. Perpetual environmentally powered sensor networks. In Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on, pages 463--468. IEEE, 2005.

Digital Library

[5]

A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava. Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4):32, 2007.

Digital Library

[6]

P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, et al. Tinyos: An operating system for sensor networks. In Ambient intelligence, pages 115--148. Springer, 2005.

[7]

C. Moser, L. Thiele, D. Brunelli, and L. Benini. Adaptive power management for environmentally powered systems. Computers, IEEE Transactions on, 59(4):478--491, 2010.

Digital Library

[8]

D. Porcarelli, D. Brunelli, and L. Benini. Improving the efficiency of air-flow energy harvesters combining active and passive rectifiers. In Proceedings of the 1st International Workshop on Energy Neutral Sensing Systems, page 6. ACM, 2013.

Digital Library

[9]

D. Shin, Y. Kim, Y. Wang, N. Chang, and M. Pedram. Constant-current regulator-based battery-supercapacitor hybrid architecture for high-rate pulsed load applications. Journal of Power Sources, 205:516--524, 2012.

[10]

F. Simjee and P. H. Chou. Everlast: long-life, supercapacitor-operated wireless sensor node. In Low Power Electronics and Design, 2006. ISLPED'06. Proceedings of the 2006 International Symposium on, pages 197--202. IEEE, 2006.

Digital Library

[11]

R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler. An analysis of a large scale habitat monitoring application. In Proceedings of the 2nd international conference on Embedded networked sensor systems, pages 214--226. ACM, 2004.

Digital Library

[12]

TI. MSP 430 Ultra-Low-Power Microcontrollers datasheet. www.ti.com, 2011.

[13]

U. Varshney. Pervasive healthcare and wireless health monitoring. Mobile Networks and Applications, 12(2-3):113--127, 2007.

Digital Library

[14]

C. M. Vigorito, D. Ganesan, and A. G. Barto. Adaptive control of duty cycling in energy-harvesting wireless sensor networks. In Sensor, Mesh and Ad Hoc Communications and Networks, 2007. SECON'07. 4th Annual IEEE Communications Society Conference on, pages 21--30. IEEE, 2007.

[15]

H. Yang and Y. Zhang. Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications. Journal of Power Sources, 196(20):8866--8873, 2011.

[16]

H. Yang and Y. Zhang. Analysis of supercapacitor energy loss for power management in environmentally powered wireless sensor nodes. IEEE transactions on power electronics, 28(11):5391--5403, 2013.

[17]

Y. Zhang and H. Yang. Modeling and characterization of supercapacitors for wireless sensor network applications. Journal of Power Sources, 196(8):4128--4135, 2011.

[18]

T. Zhu, A. Mishra, D. Irwin, N. Sharma, P. Shenoy, and D. Towsley. The case for efficient renewable energy management in smart homes. In Proceedings of the Third ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pages 67--72. ACM, 2011.

Digital Library

[19]

T. Zhu, Z. Zhong, Y. Gu, T. He, and Z.-L. Zhang. Leakage-aware energy synchronization for wireless sensor networks. In Proceedings of the 7th international conference on Mobile systems, applications, and services, pages 319--332. ACM, 2009.

Digital Library

Cited By

Li JSun GWang ALei MLiang SKang HLiu Y(2022)A many-objective optimization charging scheme for wireless rechargeable sensor networks via mobile charging vehiclesComputer Networks10.1016/j.comnet.2022.109196215(109196)Online publication date: Oct-2022
https://doi.org/10.1016/j.comnet.2022.109196
Ju QSun GLi HZhang Y(2019)Collaborative In-Network Processing for Internet of Battery-Less ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.28990226:3(5184-5195)Online publication date: Jun-2019
https://doi.org/10.1109/JIOT.2019.2899022
Ju QZhang Y(2018)Predictive Power Management for Internet of Battery-Less ThingsIEEE Transactions on Power Electronics10.1109/TPEL.2017.266409833:1(299-312)Online publication date: Jan-2018
https://doi.org/10.1109/TPEL.2017.2664098
Show More Cited By

Index Terms

Reducing charge redistribution loss for supercapacitor-operated energy harvesting wireless sensor nodes
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

Recommendations

Research of Wireless Sensor Network Nodes Based on Ambient Energy Harvesting
ICINIS '13: Proceedings of the 2013 6th International Conference on Intelligent Networks and Intelligent Systems

The use of disposable battery in wireless sensor network (WSN) nodes limits the performance of wireless sensor network and the life of network, also increases the cost of the network. With energy technology that converts ambient energy (light, heat, ...
Wireless sensor networks with energy harvesting technologies: a game-theoretic approach to optimal energy management

Energy harvesting technologies are required for autonomous sensor networks for which using a power source from a fixed utility or manual battery recharging is infeasible. An energy harvesting device (e.g., a solar cell) converts different forms of ...
A new clustering protocol for energy harvesting-wireless sensor networks

Consider the challenge of increased Throughput in Energy Harvesting Wireless Sensor Networks.Formulating the problem by taking the sunlight energy harvesting to improve the efficiency under energy harvesting restrictions.Proposing a multi-stage unequal ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ENSsys '14: Proceedings of the 2nd International Workshop on Energy Neutral Sensing Systems

November 2014

63 pages

ISBN:9781450331890

DOI:10.1145/2675683

General Chair:
Geoff V. Merrett
University of Southampton, UK

Copyright © 2014 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 ACM 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Division of Computer and Network Systems

Conference

SenSys '14

Sponsor:

SenSys '14: The 12th ACM Conference on Embedded Network Sensor Systems

November 6, 2014

Tennessee, Memphis

Acceptance Rates

Overall Acceptance Rate 21 of 29 submissions, 72%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
146
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 14 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Li JSun GWang ALei MLiang SKang HLiu Y(2022)A many-objective optimization charging scheme for wireless rechargeable sensor networks via mobile charging vehiclesComputer Networks10.1016/j.comnet.2022.109196215(109196)Online publication date: Oct-2022
https://doi.org/10.1016/j.comnet.2022.109196
Ju QSun GLi HZhang Y(2019)Collaborative In-Network Processing for Internet of Battery-Less ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.28990226:3(5184-5195)Online publication date: Jun-2019
https://doi.org/10.1109/JIOT.2019.2899022
Ju QZhang Y(2018)Predictive Power Management for Internet of Battery-Less ThingsIEEE Transactions on Power Electronics10.1109/TPEL.2017.266409833:1(299-312)Online publication date: Jan-2018
https://doi.org/10.1109/TPEL.2017.2664098
Ju QZhang Y(2017)Clustered Data Collection for Internet of Batteryless ThingsIEEE Internet of Things Journal10.1109/JIOT.2017.27608554:6(2275-2285)Online publication date: Dec-2017
https://doi.org/10.1109/JIOT.2017.2760855
Ju QZhang Y(2016)Charge Redistribution-Aware Power Management for Supercapacitor-Operated Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2015.251097616:7(2046-2054)Online publication date: Apr-2016
https://doi.org/10.1109/JSEN.2015.2510976

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 Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents