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Harvesting-Aware Optimal Communication Scheme for Infrastructure-Less Sensing

Authors:

Lothar ThieleAuthors Info & Claims

ACM Transactions on Internet of Things, Volume 1, Issue 4

Article No.: 22, Pages 1 - 26

https://doi.org/10.1145/3395928

Published: 21 June 2020 Publication History

Abstract

Sensing systems for long-term monitoring constitute an important part of the emerging Internet of Things. In this domain, energy harvesting and infrastructure-less communication enable truly autonomous and maintenance-free operation of sensor nodes gathering long-term environmental data. Due to the infrastructure-less nature of the communication, receivers are not always available. The variable energy provided by the environment and the receiver’s mobility lead to non-deterministic node availability. In this work, we study infrastructure-less data transmission schemes to optimize communication when both senders and receivers exhibit intermittent behavior. We rely on the notion of data utility, describing the importance of sensed data to the receiver, to determine an optimal communication scheme. Deriving the communication policy that maximizes the utility of the received data is shown to be a convex optimization problem. The resulting scheme is implemented and validated on a batteryless Bluetooth Low Energy sensor node that communicates to commodity smartphones. Our evaluation demonstrates that the model accurately captures the application scenario with a maximum root-mean-square error of less than 0.016 in data reception probability. The communication scheme’s adaptiveness to variable harvesting conditions is experimentally demonstrated under varying harvesting conditions and is shown to significantly increase the data utility.

References

[1]

Rehan Ahmed, Bernhard Buchli, Stefan Draskovic, Lukas Sigrist, Pratyush Kumar, and Lothar Thiele. 2019. Optimal power management with guaranteed minimum energy utilization for solar energy harvesting systems. ACM Transactions on Embedded Computing Systems 18, 4 (June 2019), 1--26.

[2]

D. Balsamo, A. S. Weddell, A. Das, A. R. Arreola, D. Brunelli, B. M. Al-Hashimi, G. V. Merrett, and L. Benini. 2016. Hibernus++: A self-calibrating and adaptive system for transiently-powered embedded devices. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35, 12 (2016), 1968--1980.

Digital Library

[3]

Naveed Anwar Bhatti, Muhammad Hamad Alizai, Affan A. Syed, and Luca Mottola. 2016. Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences. ACM Transactions on Sensor Networks 12, 3 (Aug. 2016), Article 24, 40 pages.

Digital Library

[4]

Naveed Anwar Bhatti and Luca Mottola. 2017. HarvOS: Efficient code instrumentation for transiently-powered embedded sensing. In Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN ’17). 209--219.

Digital Library

[5]

Davis Blalock, Samuel Madden, and John Guttag. 2018. Sprintz: Time series compression for the Internet of Things. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 3 (Sept. 2018), 1--23.

Digital Library

[6]

Stephen Boyd and Lieven Vandenberghe. 2004. Convex Optimization. Cambridge University Press, Cambridge, UK.

[7]

Bernhard Buchli, Felix Sutton, Jan Beutel, and Lothar Thiele. 2014. Towards enabling uninterrupted long-term operation of solar energy harvesting embedded systems. In Proceedings of the 11th European Conference on Wireless Sensor Networks (EWSN ’14). 66--83.

[8]

N. Bulusu, J. Heidemann, and D. Estrin. 2000. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications 7, 5 (Oct. 2000), 28--34.

[9]

E. J. Candes and M. B. Wakin. 2008. An introduction to compressive sampling. IEEE Signal Processing Magazine 25, 2 (March 2008), 21--30.

[10]

Alexei Colin, Emily Ruppel, and Brandon Lucia. 2018. A reconfigurable energy storage architecture for energy-harvesting devices. In Proceedings of the 23rd International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’18). ACM, New York, NY, 767--781.

[11]

Y. Collet and M. Kucherawy. 2018. Zstandard Compression and the Application/Zstd Media Type. Technical Report RFC8478. RFC Editor.

[12]

A. Dunkels, B. Gronvall, and T. Voigt. 2004. Contiki—A lightweight and flexible operating system for tiny networked sensors. In Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks. 455--462.

Digital Library

[13]

Songtao Feng and Jing Yang. 2018. Optimal status updating for an energy harvesting sensor with a noisy channel. In Proceedings of the 2018 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS ’18). IEEE, Los Alamitos, CA, 348--353.

[14]

Andres Gomez, Lukas Sigrist, Thomas Schalch, Luca Benini, and Lothar Thiele. 2017. Efficient, long-term logging of rich data sensors using transient sensor nodes. ACM Transactions on Embedded Computing Systems 17, 1 (Sept. 2017), Article 4, 23 pages.

[15]

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

Digital Library

[16]

Josiah Hester, Kevin Storer, and Jacob Sorber. 2017. Timely execution on intermittently powered batteryless sensors. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems (SenSys ’17). ACM, New York, NY, 1--13.

Digital Library

[17]

Josiah Hester, Nicole Tobias, Amir Rahmati, Lanny Sitanayah, Daniel Holcomb, Kevin Fu, Wayne P. Burleson, and Jacob Sorber. 2016. Persistent clocks for batteryless sensing devices. ACM Transactions on Embedded Computing Systems 15, 4 (Aug. 2016), Article 77, 28 pages.

Digital Library

[18]

Anwar Hithnawi, Hossein Shafagh, and Simon Duquennoy. 2015. TIIM: Technology-independent interference mitigation for low-power wireless networks. In Proceedings of the 14th International Conference on Information Processing in Sensor Networks (IPSN’15). ACM, New York, NY, 1--12.

[19]

Hrishikesh Jayakumar, Arnab Raha, Woo Suk Lee, and Vijay Raghunathan. 2015. QuickRecall: A HW/SW approach for computing across power cycles in transiently powered computers. ACM Journal on Emerging Technologies in Computing Systems 12, 1 (Aug. 2015), 1--19.

Digital Library

[20]

Philo Juang, Hidekazu Oki, Yong Wang, Margaret Martonosi, Li Shiuan Peh, and Daniel Rubenstein. 2002. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with ZebraNet. ACM SIGARCH Computer Architecture News 30, 5 (Dec. 2002), 96--107.

Digital Library

[21]

Aman Kansal, Jason Hsu, Sadaf Zahedi, and Mani B. Srivastava. 2007. Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems 6, 4 (Sept. 2007), 1--32.

Digital Library

[22]

J. E. Kim, T. Abdelzaher, L. Sha, A. Bar-Noy, and R. Hobbs. 2016. Sporadic decision-centric data scheduling with normally-off sensors. In Proceedings of the 2016 IEEE Real-Time Systems Symposium (RTSS’16). IEEE, Los Alamitos, CA, 135--145.

[23]

Giang Truong Le, Thang Viet Tran, Hyeon-Sock Lee, and Wan-Young Chung. 2016. Long-range batteryless RF sensor for monitoring the freshness of packaged vegetables. Sensors and Actuators A: Physical 237 (Jan. 2016), 20--28.

[24]

Mengjuan Liu, Yan Yang, and Zhiguang Qin. 2011. A survey of routing protocols and simulations in delay-tolerant networks. In Wireless Algorithms, Systems, and Applications. Lecture Notes in Computer Science, Vol. 6843. Springer, 243--253.

[25]

Robert Margolies, Peter Kinget, Ioannis Kymissis, Gil Zussman, Maria Gorlatova, John Sarik, Gerald Stanje, et al. 2015. Energy-harvesting active networked tags (EnHANTs): Prototyping and experimentation. ACM Transactions on Sensor Networks 11, 4 (Nov. 2015), 1--27.

Digital Library

[26]

R. J. E. Merry. 2005. Wavelet Theory and Applications—A Literature Study. Technical Report DCT 2005.53. Eindhoven University of Technology, Eindhoven, Netherlands.

[27]

Masateru Minami, Takashi Morito, Hiroyuki Morikawa, and Tomonori Aoyama. 2005. Solar biscuit: A battery-less wireless sensor network system for environmental monitoring applications. In Proceedings of the 2nd International Workshop on Networked Sensing Systems (INSS ’05).

[28]

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

Digital Library

[29]

Saman Naderiparizi, Aaron N. Parks, Zerina Kapetanovic, Benjamin Ransford, and Joshua R. Smith. 2015. WISPCam: A battery-free RFID camera. In Proceedings of the 2015 IEEE International Conference on RFID (RFID’15). IEEE, Los Alamitos, CA, 166--173.

[30]

Maciej Nikodem and Marek Bawiec. 2019. Experimental evaluation of advertisement-based Bluetooth Low Energy communication. Sensors 20, 1 (Dec. 2019), 107.

[31]

Paritosh Padhy, Rajdeep K. Dash, Kirk Martinez, and Nicholas R. Jennings. 2010. A utility-based adaptive sensing and multihop communication protocol for wireless sensor networks. ACM Transactions on Sensor Networks 6, 3 (June 2010), 1--39.

[32]

Majharul Islam Rajib and Asis Nasipuri. 2017. Predictive retransmissions for intermittently connected sensor networks with transmission diversity. ACM Transactions on Embedded Computing Systems 17, 1 (Sept. 2017), 1--25.

[33]

Benjamin Ransford, Jacob Sorber, and Kevin Fu. 2011. Mementos: System support for long-running computation on RFID-scale devices. In Proceedings of the 16th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’11). ACM, New York, NY, 159--170.

Digital Library

[34]

M. A. Razzaque, Chris Bleakley, and Simon Dobson. 2013. Compression in wireless sensor networks: A survey and comparative evaluation. ACM Transactions on Sensor Networks 10, 1 (Nov. 2013), Article 5, 44 pages.

Digital Library

[35]

Christopher M. Sadler and Margaret Martonosi. 2006. Data compression algorithms for energy-constrained devices in delay tolerant networks. In Proceedings of the 4th ACM Conference on Embedded Network Sensor Systems (SenSys’06). ACM, New York, NY, 265--278.

[36]

Gaoyang Shan and Byeong-Hee Roh. 2018. Advertisement interval to minimize discovery time of whole BLE advertisers. IEEE Access 6 (2018), 17817--17825.

[37]

Lukas Sigrist, Andres Gomez, Roman Lim, Stefan Lippuner, Matthias Leubin, and Lothar Thiele. 2017. Measurement and validation of energy harvesting IoT devices. In Proceedings of the 2017 Design, Automation, and Test in Europe Conference and Exhibition (DATE’17). IEEE, Los Alamitos, CA, 1159--1164.

[38]

Jacob Sorber, Aruna Balasubramanian, Mark D. Corner, Joshua R. Ennen, and Carl Qualls. 2013. Tula: Balancing energy for sensing and communication in a perpetual mobile system. IEEE Transactions on Mobile Computing 12, 4 (April 2013), 804--816.

[39]

Thrasyvoulos Spyropoulos, Konstantinos Psounis, and Cauligi S. Raghavendra. 2005. Spray and wait: An efficient routing scheme for intermittently connected mobile networks. In Proceedings of the 2005 ACM SIGCOMM Workshop on Delay-Tolerant Networking (WDTN’05). ACM, New York, NY, 252--259.

[40]

Sennur Ulukus, Aylin Yener, Elza Erkip, Osvaldo Simeone, Michele Zorzi, Pulkit Grover, and Kaibin Huang. 2015. Energy harvesting wireless communications: A review of recent advances. IEEE Journal on Selected Areas in Communications 33, 3 (March 2015), 360--381.

[41]

Ricklef Wohlers, Niki Trigoni, Rui Zhang, and Stephen Ellwood. 2009. TwinRoute: Energy-efficient data collection in fixed sensor networks with mobile sinks. In Proceedings of the 10th International Conference on Mobile Data Management: Systems, Services and Middleware. IEEE, Los Alamitos, CA, 192--201.

[42]

Sheng Yu, Baoxian Zhang, Cheng Li, and Hussein Mouftah. 2014. Routing protocols for wireless sensor networks with mobile sinks: A survey. IEEE Communications Magazine 52, 7 (July 2014), 150--157.

[43]

Jianhui Zhang, Zhi Li, and Shaojie Tang. 2016. Value of information aware opportunistic duty cycling in solar harvesting sensor networks. IEEE Transactions on Industrial Informatics 12, 1 (Feb. 2016), 348--360.

[44]

Pengyu Zhang, Deepak Ganesan, and Boyan Lu. 2013. QuarkOS: Pushing the operating limits of micro-powered sensors. In Proceedings of the 14th USENIX Conference on Hot Topics in Operating Systems.

Cited By

Kenyeres MKenyeres JHassankhani Dolatabadi S(2025)Distributed Consensus Gossip-Based Data Fusion for Suppressing Incorrect Sensor Readings in Wireless Sensor NetworksJournal of Low Power Electronics and Applications10.3390/jlpea1501000615:1(6)Online publication date: 26-Jan-2025
https://doi.org/10.3390/jlpea15010006
Babatunde SAlsubhi AHester JSorber J(2024)Greentooth: Robust and Energy Efficient Wireless Networking for Batteryless DevicesACM Transactions on Sensor Networks10.1145/364922120:3(1-31)Online publication date: 13-Apr-2024
https://dl.acm.org/doi/10.1145/3649221
Longman EEl-Hajjar MMerrett GGummeson JLee SGao JXing G(2022)Multihop Networking for Intermittent DevicesProceedings of the 20th ACM Conference on Embedded Networked Sensor Systems10.1145/3560905.3568104(878-884)Online publication date: 6-Nov-2022
https://dl.acm.org/doi/10.1145/3560905.3568104
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Published In

cover image ACM Transactions on Internet of Things

ACM Transactions on Internet of Things Volume 1, Issue 4

November 2020

181 pages

EISSN:2577-6207

DOI:10.1145/3407671

Editors:
Schahram Dustdar
TU Wien, Austria
,
Gian Pietro Picco
University of Trento, Italy

Issue’s Table of Contents

Copyright © 2020 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].

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 21 June 2020

Online AM: 07 May 2020

Accepted: 01 April 2020

Revised: 01 March 2020

Received: 01 August 2019

Published in TIOT Volume 1, Issue 4

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Cited By

Kenyeres MKenyeres JHassankhani Dolatabadi S(2025)Distributed Consensus Gossip-Based Data Fusion for Suppressing Incorrect Sensor Readings in Wireless Sensor NetworksJournal of Low Power Electronics and Applications10.3390/jlpea1501000615:1(6)Online publication date: 26-Jan-2025
https://doi.org/10.3390/jlpea15010006
Babatunde SAlsubhi AHester JSorber J(2024)Greentooth: Robust and Energy Efficient Wireless Networking for Batteryless DevicesACM Transactions on Sensor Networks10.1145/364922120:3(1-31)Online publication date: 13-Apr-2024
https://dl.acm.org/doi/10.1145/3649221
Longman EEl-Hajjar MMerrett GGummeson JLee SGao JXing G(2022)Multihop Networking for Intermittent DevicesProceedings of the 20th ACM Conference on Embedded Networked Sensor Systems10.1145/3560905.3568104(878-884)Online publication date: 6-Nov-2022
https://dl.acm.org/doi/10.1145/3560905.3568104
Melo BAndrade RDarin TSantos CBento Villela MRios da Hora Rodrigues Kde Gois Ribeiro Darin T(2022)Longitudinal user experience studies in the IoT domainProceedings of the 21st Brazilian Symposium on Human Factors in Computing Systems10.1145/3554364.3559135(1-13)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3554364.3559135
Gomez ATretter AHager PSanmugarajah PBenini LThiele L(2022)Dataflow Driven Partitioning of Machine Learning Applications for Optimal Energy Use in Batteryless SystemsACM Transactions on Embedded Computing Systems10.1145/352013521:5(1-29)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3520135
de Winkel JTang HPawełczak PBulusu NAryafar EBalasubramanian ASong J(2022)Intermittently-powered bluetooth that worksProceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services10.1145/3498361.3538934(287-301)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1145/3498361.3538934
Ahmed RDraskovic SThiele L(2022)Stochastic Guarantees for Adaptive Energy Harvesting SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.319851941:11(3614-3625)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1109/TCAD.2022.3198519
Stricker NAlbert JRabbani MMayer SGomez A(2022)Secure Communication with Batteryless Sensors2022 11th Mediterranean Conference on Embedded Computing (MECO)10.1109/MECO55406.2022.9797104(1-4)Online publication date: 7-Jun-2022
https://doi.org/10.1109/MECO55406.2022.9797104
Rufer LStricker NDa Forno RThiele LGomez A(2022)Demo Abstract: DPP3e: A Harvesting-based Dual Processor Platform for Advanced Indoor Environmental Sensing2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)10.1109/IPSN54338.2022.00048(495-496)Online publication date: May-2022
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Bradbury MJhumka AWatson T(2022)Information management for trust computation on resource-constrained IoT devicesFuture Generation Computer Systems10.1016/j.future.2022.05.004135:C(348-363)Online publication date: 1-Oct-2022
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