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Near-Optimal Co-Deployment of Chargers and Sink Stations in Rechargeable Sensor Networks

Published: 29 August 2017 Publication History

Abstract

Wireless charging technology has drawn great attention of both academia and industry in recent years, due to its potential of significantly improving the system performance of sensor networks. The emergence of an open-source experimental platform for wireless rechargeable sensor networks, Powercast, has made the theoretical research closer to reality. This pioneering platform is able to recharge sensor nodes much more efficiently and allows different communication protocols to be implemented upon users’ demands. Different from the RFID-based model widely used in the existing works, Powercast designs the charger and sink station separately. This leads to a new design challenge of cooperatively deploying minimum number of chargers and sink stations in wireless rechargeable sensor networks. Such a co-deployment issue is extremely challenging, since the deployments of chargers and sink stations are coupled, and each subproblem is known to be NP-hard. The key to the design is to understand the intrinsic relationship between data flow and energy flow, which is interdependent. In this article, we tackle this challenge by dividing it into two subproblems and optimizing charger and sink station deployment iteratively. Specifically, we first transform each subproblem to a max-flow problem. With this, we are able to select chargers or sink stations according to their contributions to the total flow rate. We design greedy-based algorithms with a guaranteed worst-case bound ln R/ξ for the subproblems of charger deployment and sink station deployment, respectively. Further, we address the original problem by designing an iterative algorithm that solves two subproblems alternatively to achieve a near optimal performance. We corroborate our analysis by extensive simulations under practical coefficient settings and demonstrate the advantage of the proposed algorithm.

References

[1]
A. Bogdanov, E. Maneva, and S. Riesenfeld. 2004. Power-aware base station positioning for sensor networks. In Proceedings of the 23rd Conference of the IEEE Communications Society. IEEE.
[2]
H. Dai, X. Wu, G. Chen, L. Xu, and S. Lin. 2014. Minimizing the number of mobile chargers for large-scale wireless rechargeable sensor networks. Comput. Commun. 46 (2014), 54--65.
[3]
R. Deng, Y. Zhang, S. He, J. Chen, and X. Shen. 2016. Maximizing network utility of rechargeable sensor networks with spatiotemporally coupled constraints. IEEE Journal on Selected Areas in Communications 34, 5 (2016), 1307--1319.
[4]
M. Dong, K. Ota, and A. Liu. 2016a. RMER: Reliable and energy-efficient data collection for large-scale wireless sensor networks. IEEE Internet of Things Journal 3, 4 (2016), 511--519.
[5]
M. Dong, K. Ota, A. Liu, and M. Guo. 2016b. Joint optimization of lifetime and transport delay under reliability constraint wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems 27, 1 (2016), 225--236.
[6]
L. Fu, P. Cheng, Y. Gu, J. Chen, and T. He. 2013. Minimizing charging delay in wireless rechargeable sensor networks. In Proceedings of the 32nd IEEE International Conference on Computer Communications. IEEE, Turin.
[7]
P. Gonzalez-Brevis, J. Gondzio, Y. Fan, H. Poor, J. Thompson, I. Krikidis, and P. J. Chung. 2011. Base station location optimization for minimal energy consumption in wireless networks. In Proceedings of the 73rd IEEE Vehicular Technology Conference. IEEE.
[8]
S. Guo, C. Wang, and Y. Yang. 2014. Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mobile Comput. 13, 12 (2014), 2836--2852.
[9]
S. He, J. Chen, F. Jiang, D. Yau, G. Xing, and Y. Sun. 2012. Energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mobile Comput. 12, 10 (2012), 1931--1942.
[10]
S. He, D.-H. Shin, J. Zhang, J. Chen, and Y. Sun. 2016. Full-view area coverage in camera sensor networks: Dimension reduction and near-optimal solutions. IEEE Trans.n Vehic. Technol. 65, 9 (2016), 7448--7461.
[11]
W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. 2000. Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. IEEE.
[12]
A. Kurs, A. Karalis, R. Moffatt, J. Joannopoulos, P. Fisher, and M. Soljai. 2007. Wireless power transfer via strongly coupled magnetic resonances. Science 317, 5834 (2007), 83--86.
[13]
J. H. Liao, W. T. So, and J. R. Jiang. 2013. Optimized charger deployment for wireless rechargeable sensor networks. In Proceedings of the 9th Workshop on Wireless, Ad hoc, and Sensor Networks. Retrieved from http://wasn2013.cs.nthu.edu.tw/paper_result.php.
[14]
H. Liu. 2011. Retrieved from http://hxhl95.github.io/media/ib_ee.pdf.
[15]
J. Long, A. Liu, M. Dong, and Z. Li. 2016. An energy-efficient and sink location privacy enhanced scheme for WSNs through ring based routing. J. Parallel and Distrib. Comput. 81 (2016), 47--65.
[16]
X. Lu, P. Wang, D. Niyato, D. I. Kim, and Z. Han. 2015. Wireless networks with RF energy harvesting: A contemporary survey. IEEE Commun. Surveys Tutor. 17, 2 (2015), 757--789.
[17]
J. Luo and J. Hubaux. 2005. Joint mobility and routing for lifetime elongation in wireless sensor networks. In Proceedings of the 24th IEEE Annual Joint Conference of Computer and Communications Societies. IEEE.
[18]
C. Mikeka and H. Arai. 2011. Design Issues in Radio Frequency Energy Harvesting System. INTECH Open Access Publisher.
[19]
E. Modiano, D. Shah, and G. Zussman. 2006. Maximizing throughput in wireless networks via gossiping. In Proceedings of the Joint International Conference on Measurement and Modeling of Computer Systems. ACM.
[20]
UMich Moo. 2011. Retrieved from https://spqr.eecs.umich.edu/moo/.
[21]
Powercast. 2016. Retrieved from http://www.powercastco.com/.
[22]
L. Qiu, R. Chandra, K. Jain, and M. Mahdian. 2004. Optimizing the placement of integration points in multi-hop wireless networks. In Proceedings of the 12th International Conference on Network Protocols. IEEE, 271--282.
[23]
P. T. A. Quang and D.-S. Kim. 2012. Enhancing real-time delivery of gradient routing for industrial wireless sensor networks. IEEE Trans. Industr. Informat. 8, 1 (2012), 61--68.
[24]
S. Roy, V. Jandhyala, J. R. Smith, D. J. Wetherall, B. P. Otis, R. Chakraborty, M. Buettner, D. J. Yeager, Y.-C. Ko, and A. P. Sample. 2010. RFID: From supply chains to sensor nets. IEEE RFID Virtual J. 98, 9 (2010), 1583--1592.
[25]
A. Sample, D. Yeager, A. Mamishev P. Powledge, and J. Smith. 2008. Design of an rfid-based battery-free programmable sensing platform. IEEE Trans. Instrument. Measure. 57, 11 (2008), 2608--2615.
[26]
L. Shi, Z. Kabelac, D. Katabi, and D. Perreault. 2015. Wireless power hotspot that charges all of your devices. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. ACM, Paris.
[27]
Y. Shu, P. Cheng, Y. Gu, J. Chen, and T. He. 2014. Minimizing communication delay in RFID-based wireless rechargeable sensor networks. In Proceedings of the 2014 17th Annual IEEE International Conference on Sensing, Communication, and Networking. IEEE.
[28]
Y. Shu, P. Cheng, Y. Gu, J. Chen, and T. He. 2015. TOC: Localizing wireless rechargeable sensors with time of charge. ACM Trans. Sensor Networks 11, 3 (2015), 44.
[29]
Y. Shu, Y. Gu, and J. Chen. 2014. Dynamic authentication with sensory information for the access control systems. IEEE Trans. Parallel Distrib. Syst. 25, 2 (2014), 427--436.
[30]
J. R. Smith, K. P. Fishkin, B. Jiang, A. Mamishev, M. Philipose, A. D. Rea, S. Roy, and K. Sundara-Rajan. 2005. RFID-based techniques for human-activity detection. ACM Commun. Mag. Special Issue: RFID 48, 9 (2005), 39--44.
[31]
STLM20. 2016. Retrieved from http://www.st.com/content/st_com/zh/products/mems-and-sensors/temperature-sensors/stlm20.html.
[32]
B. Tong, Z. Li, G. Wang, and W. Zhang. 2010. How wireless power charging technology affects sensor network deployment and routing. In Proceedings of the IEEE 30th International Conference on Distributed Computing Systems. IEEE.
[33]
Z. Vincze, R. Vida, and A. Vidacs. 2007. Deploying multiple sinks in multi-hop wireless sensor networks. In Proceedings of the IEEE International Conference on Pervasive Services. IEEE.
[34]
J. Wang, A. Liu, T. Yan, and Z. Zeng. 2017a. A resource allocation model based on double-sided combinational auctions for transparent computing. Peer-to-Peer Networking and Applications 2017, to appear (2017).
[35]
Y. Wang, K. Wu, and L. Ni. 2017b. WiFall: Device-free fall detection by wireless networks. IEEE Trans. Mobile Comput. 16, 2 (2017), 581--594.
[36]
Y. Xiao, D. Niyato, Z. Han, and L. A. DaSilva. 2015. Dynamic energy trading for energy harvesting communication networks: A stochastic energy trading game. IEEE J. Select. Areas Commun. 33, 12 (2015), 2718--2734.
[37]
G. Xie, K. Ota, M. Dong, F. Pan, and A. Liu. 2016. Energy-efficient routing for mobile data collectors in wireless sensor networks with obstacles. Peer to-Peer Networking and Applications 1, 12 (2016), 472--483.
[38]
G. Yang, S. He, Z. Shi, and J. Chen. 2017. Promoting cooperation by social incentive mechanism in mobile crowdsensing. IEEE Commun. Mag. 2017, to appear (2017).
[39]
Q. Yang, S. He, J. Li, J. Chen, and Y. Sun. 2015. Energy-efficient probabilistic area coverage in wireless sensor. IEEE Trans. Vehic. Technol. 61, 1 (2015), 367--377.
[40]
R. Zhang, P. Thiran, and M. Vetterli. 2015. Virtually moving base stations for energy efficiency in wireless sensor networks. In Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM.
[41]
S. Zhang, J. Wu, and S. Lu. 2012. Collaborative mobile charging for sensor networks. In Proceedings of the IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems. IEEE.
[42]
Y. Zhang, S. He, and J. Chen. 2016. Data gathering optimization by dynamic sensing and routing in rechargeable sensor networks. IEEE/ACM Transactions on Networking 24, 3 (2016), 1632--1646.
[43]
Y. Zou, J. Xiao, K. Wu, J. Han, Y. Li, and L. Ni. 2017. GRfid: A device-free RFID-based gesture recognition system. IEEE Trans. Mobile Comput. 16, 2 (2017), 381--393.

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    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
    Issue’s Table of Contents
    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]

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    Publication History

    Published: 29 August 2017
    Accepted: 01 March 2017
    Revised: 01 December 2016
    Received: 01 June 2016
    Published in TECS Volume 17, Issue 1

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    Author Tags

    1. Wireless rechargeable sensor networks
    2. deployment cost
    3. greedy-based max-flow
    4. iterative method

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    • Zhejiang Provincial Natural Science Foundation

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    • (2024)Deployment optimization for target perpetual coverage in energy harvesting wireless sensor networkDigital Communications and Networks10.1016/j.dcan.2023.02.00910:2(498-508)Online publication date: Apr-2024
    • (2023)Application of Artificial Intelligence Technology in the Optimal Deployment of Wireless Sensor Network NodesFrontiers in Computing and Intelligent Systems10.54097/fcis.v5i2.122885:2(31-33)Online publication date: 1-Sep-2023
    • (2023)ChaseCharge: Charging Sensors by Chasing in Sensor-Cloud SystemsACM Transactions on Sensor Networks10.1145/3582885Online publication date: 13-Feb-2023
    • (2023)Battery-Free Wireless Sensor Networks: A Comprehensive SurveyIEEE Internet of Things Journal10.1109/JIOT.2022.322238610:6(5543-5570)Online publication date: 15-Mar-2023
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    • (2021)Task-driven charger placement and power allocation for wireless sensor networksAd Hoc Networks10.1016/j.adhoc.2021.102556119(102556)Online publication date: Aug-2021
    • (2021)Two-phase node deployment for target coverage in rechargeable WSNs using genetic algorithm and integer linear programmingThe Journal of Supercomputing10.1007/s11227-020-03431-777:4(4172-4200)Online publication date: 1-Apr-2021
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