research-article

On the Global Maximization of Network Lifetime in Wireless Rechargeable Sensor Networks

Authors:

Minh Hieu Nguyen,

Thanh Hung Nguyen,

Phi Le NguyenAuthors Info & Claims

ACM Transactions on Sensor Networks, Volume 18, Issue 4

Article No.: 71, Pages 1 - 29

https://doi.org/10.1145/3510423

Published: 29 November 2022 Publication History

Abstract

In a Wireless Rechargeable Sensor Network (WRSN), a mobile charger (MC) moves and supplies energy for sensor nodes to maintain the network operation. Hence, optimizing the charging schedule of MC is essential to maximize the network lifetime in WRSNs. The existing works only target the local optimization of network lifetime limited to MC’s subsequent charging round. The network lifetime has been normally reflected in a different metric that is not directly related to the final charging round period. To the best of our knowledge, this work is the first to address the global maximization of network lifetime in WRSNs, which optimizes not only the subsequent charging round but all charging rounds over the entire network lifetime. Another uniqueness is the joint consideration of both the charging path and charging time optimization problems. As a solution, we propose a genetic algorithm (GA)-based global optimization scheme that considers all the possible charging rounds. The GA has a novel mutation operation that mutates gene sizes for representing charging schedules with a varying number of charging rounds. The experiment results show that our algorithm can extend the network lifetime by 35.1 times on average and 38.6 times in the best case compared to existing ones.

References

[1]

Mostafa Z. Ali, Noor H. Awad, Ponnuthurai N. Suganthan, Ali M. Shatnawi, and Robert G. Reynolds. 2018. An improved class of real-coded genetic algorithms for numerical optimization✰. Neurocomputing 275 (2018), 155–166.

Digital Library

[2]

Mahima Arrawatia, Maryam Shojaei Baghini, and Girish Kumar. 2015. Differential microstrip antenna for RF energy harvesting. IEEE Trans. Anten. Propagat. 63, 4 (2015), 1581–1588.

[3]

Xianbo Cao, Wenzheng Xu, Xuxun Liu, Jian Peng, and Tang Liu. 2020. A deep reinforcement learning-based on-demand charging algorithm for wireless rechargeable sensor networks. Ad Hoc Netw. 110 (2020), 102278.

[4]

Haipeng Dai, Ke Sun, Alex X. Liu, Lijun Zhang, Jiaqi Zheng, and Guihai Chen. 2018. Charging task scheduling for directional wireless charger networks. In Proceedings of the 47th International Conference on Parallel Processing (ICPP’18). Article 10, 10 pages.

Digital Library

[5]

Xingjian Ding, JianXiong Guo, Yongcai Wang, Deying Li, and Weili Wu. 2021. Task-driven charger placement and power allocation for wireless sensor networks. Ad Hoc Netw. 119 (2021), 102556.

[6]

Yong Feng, Nianbo Liu, Feng Wang, Qian Qian, and Xiuqi Li. 2016. Starvation avoidance mobile energy replenishment for wireless rechargeable sensor networks. In Proceedings of the IEEE International Conference on Communications (ICC’16). 1–6.

[7]

L. Fu, P. Cheng, Y. Gu, J. Chen, and T. He. 2016. Optimal charging in wireless rechargeable sensor networks. IEEE Trans. Vehic. Technol. 65, 1 (2016), 278–291.

[8]

L. Fu, P. Cheng, Y. Gu, J. Chen, and T. He. 2016. Optimal charging in wireless rechargeable sensor networks. IEEE Trans. Vehic. Technol. 65, 1 (Jan.2016), 278–291.

[9]

Niayesh Gharaei, Yasser D. Al-Otaibi, Suhail Ashfaq Butt, Sharaf Jameel Malebary, Sabit Rahim, and Gul Sahar. 2021. Energy-Efficient tour optimization of wireless mobile chargers for rechargeable sensor networks. IEEE Syst. J. 15, 1 (2021), 27–36.

[10]

G. Han, X. Yang, L. Liu, S. Chan, and W. Zhang. 2019. A coverage-aware hierarchical charging algorithm in wireless rechargeable sensor networks. IEEE Netw. 33, 4 (2019), 201–207.

[11]

S. He, J. Chen, F. Jiang, D. K. Y. Yau, G. Xing, and Y. Sun. 2013. Energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mobile Comput. 12, 10 (Oct.2013), 1931–1942.

Digital Library

[12]

C. Hu and Y. Wang. 2015. Minimizing the number of mobile chargers in a large-scale wireless rechargeable sensor network. In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC’15). 1297–1302.

[13]

ILOG CPLEX Optimization Studio. ILOG CPLEX Optimization Studio. Retrieved from https://www.ibm.com/products/ilog-cplex-optimization-studio.

[14]

G. Jiang, S. Lam, Y. Sun, L. Tu, and J. Wu. 2017. Joint charging tour planning and depot positioning for wireless sensor networks using mobile chargers. IEEE/ACM Trans. Netw. 25, 4 (Aug.2017), 2250–2266.

Digital Library

[15]

Amar Kaswan, Abhinav Tomar, and Prasanta K. Jana. 2018. An efficient scheduling scheme for mobile charger in on-demand wireless rechargeable sensor networks. J. Netw. Comput. Appl. 114 (2018), 123–134.

Digital Library

[16]

A. Kurs, A. Karalis, R. Moffatt and J. Joannopoulos, P. Fisher, and M. Soljacic. 2001. Wireless power transfer via strongly coupled magnetic resonances. Science 9, 1 (2001), 64–76.

[17]

Weifa Liang, Wenzheng Xu, Xiaojiang Ren, Xiaohua Jia, and Xiaola Lin. 2016. Maintaining large-scale rechargeable sensor networks perpetually via multiple mobile charging vehicles. ACM Trans. Sen. Netw. 12, 2, Article 14 (May2016), 26 pages.

Digital Library

[18]

C. Lin, F. Gao, H. Dai, J. Ren, L. Wang, and G. Wu. 2020. Maximizing charging utility with obstacles through fresnel diffraction model. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’20). 2046–2055.

Digital Library

[19]

Chi Lin, Yu Sun, Kai Wang, Zhunyue Chen, Bo Xu, and Guowei Wu. 2019. Double warning thresholds for preemptive charging scheduling in wireless rechargeable sensor networks. Comput. Netw. 148 (2019), 72–87.

[20]

C. Lin, Z. Wang, J. Deng, L. Wang, J. Ren, and G. Wu. 2018. mTS: Temporal-and spatial-collaborative charging for wireless rechargeable sensor networks with multiple vehicles. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’18). 99–107.

Digital Library

[21]

Chi Lin, Ziwei Yang, Haipeng Dai, Liangxian Cui, Lei Wang, and Guowei Wu. 2021. Minimizing charging delay for directional charging. IEEE/ACM Trans. Netw. 29, 6 (2021), 2478–2493.

Digital Library

[22]

C. Lin, J. Zhou, C. Guo, H. Song, G. Wu, and M. S. Obaidat. 2018. TSCA: A temporal-spatial real-time charging scheduling algorithm for on-demand architecture in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 17, 1 (Jan.2018), 211–224.

[23]

C. Lin, Y. Zhou, F. Ma, J. Deng, L. Wang, and G. Wu. 2019. Minimizing charging delay for directional charging in wireless rechargeable sensor networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’19). 1819–1827.

Digital Library

[24]

T. Liu, B. Wu, S. Zhang, J. Peng, and W. Xu. 2020. An effective multi-node charging scheme for wireless rechargeable sensor networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’20). 2026–2035.

Digital Library

[25]

J. Luo and J. Hubaux. 2010. Joint sink mobility and routing to maximize the lifetime of wireless sensor networks: The case of constrained mobility. IEEE/ACM Trans. Netw. 18, 3 (June2010), 871–884.

Digital Library

[26]

Zengwei Lyu, Zhenchun Wei, Jie Pan, Hua Chen, Chengkai Xia, Jianghong Han, and Lei Shi. 2019. Periodic charging planning for a mobile WCE in wireless rechargeable sensor networks based on hybrid PSO and GA algorithm. Appl. Soft Comput. 75 (2019), 388–403.

[27]

Y. Ma, W. Liang, and W. Xu. 2018. Charging utility maximization in wireless rechargeable sensor networks by charging multiple sensors simultaneously. IEEE/ACM Trans. Netw. 26, 4 (Aug.2018), 1591–1604.

Digital Library

[28]

S. Malebary. 2020. Wireless mobile charger excursion optimization algorithm in wireless rechargeable sensor networks. IEEE Sensors J. 20, 22 (2020), 13842–13848.

[29]

W. Ouyang, X. Liu, M. Obaidat, C. Lin, H. Zhou, T. Liu, and K. Hsiao. 2020. Utility-Aware charging scheduling for multiple mobile chargers in large-scale wireless rechargeable sensor networks. IEEE Trans. Sustain. Comput. 6, 4 (2020), 1.

[30]

Chulsung Park and Pai H. Chou. 2006. AmbiMax: Autonomous energy harvesting platform for multi-supply wireless sensor nodes. In Proceedings of the 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, Vol. 1. 168–177.

[31]

S. Picek, D. Jakobovic, and M. Golub. 2013. On the recombination operator in the real-coded genetic algorithms. In Proceedings of the IEEE Congress on Evolutionary Computation. 3103–3110.

[32]

Vijay Raghunathan, A. Kansal, J. Hsu, J. Friedman, and Mani Srivastava. 2005. Design considerations for solar energy harvesting wireless embedded systems. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (ISPN’05).457–462.

[33]

Abhinav Tomar, Lalatendu Muduli, and Prasanta K. Jana. 2019. An efficient scheduling scheme for on-demand mobile charging in wireless rechargeable sensor networks. Pervas. Mob. Comput. 59 (2019), 101074.

Digital Library

[34]

T. Wu, P. Yang, H. Dai, W. Xu, and M. Xu. 2019. Collaborated tasks-driven mobile charging and scheduling: A near optimal result. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’19). 1810–1818.

Digital Library

[35]

Liguang Xie, Yi Shi, Y. Thomas Hou, Wenjing Lou, Hanif D. Sherali, and Scott F. Midkiff. 2015. Multi-Node wireless energy charging in sensor networks. IEEE/ACM Trans. Netw. 23, 2 (2015), 437–450.

Digital Library

[36]

Wenzheng Xu, Weifa Liang, Xiaohua Jia, and Zichuan Xu. 2016. Maximizing sensor lifetime in a rechargeable sensor network via partial energy charging on sensors. In Proceedings of the 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON’16). 1–9.

Digital Library

[37]

W. Xu, W. Liang, H. Kan, Y. Xu, and X. Zhang. 2019. Minimizing the longest charge delay of multiple mobile chargers for wireless rechargeable sensor networks by charging multiple sensors simultaneously. In Proc. IEEE ICDCS. 881–890.

[38]

Panlong Yang, Tao Wu, Haipeng Dai, Xunpeng Rao, Xiaoyu Wang, Peng-Jun Wan, and Xin He. 2020. MORE: Multi-Node mobile charging scheduling for deadline constraints. ACM Trans. Sen. Netw. 17, 1, Article 7 (Nov.2020), 21 pages.

[39]

D. Yeager, P. Powledge, R. Prasad, D. Wetherall, and J. Smith. 2008. Wirelessly-Charged UHF tags for sensor data collection. In Proceedings of the IEEE International Conference on Radio Frequency Identification.

[40]

Z. Wei, F. Liu, Z. Lyu, X. Ding, L. Shi, and C. Xia.2018. Reinforcement learning for a novel mobile charging strategy in wireless rechargeable sensor networks. In Proceedings of the Conference on Wireless Algorithms, Systems, and Applications. 485–496.

[41]

Chuanxin Zhao, Hengjing Zhang, Fulong Chen, Siguang Chen, Changzhi Wu, and Taochun Wang. 2020. Spatiotemporal charging scheduling in wireless rechargeable sensor networks. Comput. Commun. 152 (2020), 155–170.

[42]

Jincheng Zhao, Guru Subramanyam, and Hailing Yue. 2020. A dual-band rectifying antenna design for RF energy harvesting. In Proceedings of the IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS’20). 415–418.

[43]

Jinqi Zhu, Yong Feng, Ming Liu, Guihai Chen, and Yongxin Huang. 2018. Adaptive online mobile charging for node failure avoidance in wireless rechargeable sensor networks. Comput. Commun. 126 (2018), 28–37.

Cited By

Liang DFeng BLiao X(2024)A Path Planning Method for Chargeable Sweep Coverage With Multiple Charging StationsIEEE Access10.1109/ACCESS.2024.337354312(34931-34941)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3373543
Shyja VRanganathan GBindhu V(2023)Link quality and energy efficient optimal simplified cluster based routing scheme to enhance lifetime for wireless body area networksNano Communication Networks10.1016/j.nancom.2023.10046537(100465)Online publication date: Sep-2023
https://doi.org/10.1016/j.nancom.2023.100465
Saravanan TSaravanakumar S(2022)Enhancing Node Lifetime in Wireless Sensor Networks using ITDMS with APTEEN Protocol2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)10.1109/ICAC3N56670.2022.10073975(1790-1794)Online publication date: 16-Dec-2022
https://doi.org/10.1109/ICAC3N56670.2022.10073975

Index Terms

On the Global Maximization of Network Lifetime in Wireless Rechargeable Sensor Networks
1. Networks

Recommendations

Distributed algorithms for network lifetime maximization in wireless visual sensor networks

Network lifetime maximization is a critical issue in wireless sensor networks since each sensor has a limited energy supply. In contrast with conventional sensor networks, video sensor nodes compress the video before transmission. The encoding process ...
A bi-level optimized charging algorithm for energy depletion avoidance in wireless rechargeable sensor networks
Abstract
In Wireless Rechargeable Sensor Networks (WRSNs), charging scheme optimization is one of the most critical issues, which plays an essential role in deciding the sensors’ lifetime. An effective charging scheme should simultaneously consider both ...
Optimization of Charging and Data Collection in Wireless Rechargeable Sensor Networks
HCC 2016: Revised Selected Papers of the Second International Conference on Human Centered Computing - Volume 9567

Wireless Rechargeable Sensor NetworksWRSNs can significantly prolong the lifetime by employing a mobile charger to replenish the depleted energy of the sensor nodes. This paper considers the scenario that the mobile charger cannot maintain full ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 18, Issue 4

November 2022

619 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3561986

Editor:
Yunhao Liu
Tsinghua University, China

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].

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 November 2022

Online AM: 23 February 2022

Accepted: 03 January 2022

Revised: 27 November 2021

Received: 29 April 2021

Published in TOSN Volume 18, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Refereed

Funding Sources

Vingroup Joint Stock Company (Vingroup JSC), Vingroup and supported by Vingroup Innovation Foundation (VINIF)
Ministry of Education and Training of Vietnam
Hanoi University of Science and Technology
Vingroup Joint Stock Company and supported by the Domestic Master/Ph.D. Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VINBIGDATA)
Vingroup Joint Stock Company and supported by the Domestic Master/Ph.D. Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VINBIGDATA)

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
387
Total Downloads

Downloads (Last 12 months)86
Downloads (Last 6 weeks)5

Reflects downloads up to 12 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Liang DFeng BLiao X(2024)A Path Planning Method for Chargeable Sweep Coverage With Multiple Charging StationsIEEE Access10.1109/ACCESS.2024.337354312(34931-34941)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3373543
Shyja VRanganathan GBindhu V(2023)Link quality and energy efficient optimal simplified cluster based routing scheme to enhance lifetime for wireless body area networksNano Communication Networks10.1016/j.nancom.2023.10046537(100465)Online publication date: Sep-2023
https://doi.org/10.1016/j.nancom.2023.100465
Saravanan TSaravanakumar S(2022)Enhancing Node Lifetime in Wireless Sensor Networks using ITDMS with APTEEN Protocol2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)10.1109/ICAC3N56670.2022.10073975(1790-1794)Online publication date: 16-Dec-2022
https://doi.org/10.1109/ICAC3N56670.2022.10073975

View Options

Get Access

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.

Full Text

View this article in Full Text.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View full text|Download PDF

View Issue’s Table of Contents