Abstract
Recent years have witnessed the advancement of Rechargeable Wireless Sensor Networks (RWSNs) for permanent environment monitoring or survey, while one fundamental problem is to find out the optimal cycle in a RWSN on the basis of Traveling Salesman Problem (TSP), to drive a Mobile Charger (MC) to periodically visit and charge the rechargeable sensor nodes. In this paper, by taking into account the uncertainties of the travel costs among the rechargeable sensor nodes, we investigate the so-called Sequential Mobile Charging (SMC) problem, where the MC sequentially travels along the cycles, towards the minimization of the resulting expected cumulative travel cost without being aware of the travel cost assignment. By leveraging a Multi-Armed Bandit (MAB) framework, we propose a learning-aided mobile charger scheduling algorithm, namely “BanditCharger”, which induces a regret growing logarithmically with respect to the number of the sequential cycles. The efficacy of BanditCharger also can be verified by extensive simulations
This work is partially supported by National Key R&D Program of China (Grant No. 2019YFB2102600), NSFC (Grant No. 61702304, 61971269, 61832012), Shandong Provincial Natural Science Foundation (Grant No. ZR2017QF005), and Industrial Internet Innovation and Development Project in 2019 of China.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
We will discuss the choices of the TSP solvers later in Sect. 5.
References
Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2–3), 235–256 (2002). https://doi.org/10.1023/A:1013689704352
Chen, F., et al.: Speed control of mobile chargers serving wireless rechargeable networks. Future Gener. Comput. Syst. 80, 242–249 (2018)
Chen, F., Zhao, Z., Min, G., Wu, Y.: A novel approach for path plan of mobile chargers in wireless rechargeable sensor networks. In: Proceeding of the 12th MSN, pp. 63–68 (2016)
He, L., et al.: Esync: an energy synchronized charging protocol for rechargeable wireless sensor networks. In: Proceedings of the 15th ACM MobiHoc, pp. 247–256 (2014)
Kurs, A., Karalis, A., Moffatt, R., Joannopoulos, J., Fisher, P., Soljačić, M.: Wireless power transfer via strongly coupled magnetic resonances. Science 317(5834), 83–86 (2007)
Kurs, A., Moffatt, R., Soljačić, M.: Simultaneous mid-range power transfer to multiple devices. Appl. Phys Lett. 96(4), 044102 (2010)
Li, F., Yang, Y., Chi, Z., Zhao, L., Yang, Y., Luo, J.: Trinity: enabling self-sustaining WSNS indoors with energy free sensing and networking. ACM Trans Embedded Comput. Syst. 17(2), 57:1–57:27 (2018)
Li, F., Yu, D., Yang, H., Yu, J., Karl, H., Cheng, X.: Multi-armed-bandit-based spectrum scheduling algorithms in wireless networks: a survey. IEEE Wireless Commun. 27(1), 24–30 (2020)
Lin, C., Han, D., Deng, J., Wu, G.: P\({}^{\text{2}}\)S: a primary and passer-by scheduling algorithm for on-demand charging architecture in wireless rechargeable sensor networks. IEEE Trans. Veh. Technol. 66(9), 8047–8058 (2017)
Ma, Y., Liang, W., Xu, W.: Charging utility maximization in wireless rechargeable sensor networks by charging multiple sensors simultaneously. IEEE/ACM Trans Network. 26(4), 1591–1604 (2018)
Martin, P., Charbiwala, Z., Srivastava, M.: DoubleDip: leveraging thermoelectric harvesting for low power monitoring of sporadic water use. In: Proceedings of the 10th ACM SenSys, pp. 225–238 (2012)
Shi, T., Cheng, S., Li, J., Gao, H., Cai, Z.: Dominating sets construction in RF-based battery-free sensor networks with full coverage guarantee. ACM Trans Sensor Netw 15(4), 43:1–43:29 (2019)
Shi, T., Li, J., Gao, H., Cai, Z.: Coverage in Battery-Free Wireless Sensor Networks. In: Proceedings of IEEE INFOCOM, pp. 108–116 (2018)
Shi, Y., Xie, L., Hou, Y., Sherali, H.: On renewable sensor networks with wireless energy transfer. In: Proceedings of IEEE INFOCOM, pp. 1350–1358 (2011)
Talla, V., Kellogg, B., Ransford, B., Naderiparizi, S., Gollakota, S.: Powering the Next Billion Devices with WiFi. In: Proceedings of the 11th ACM CoNEXT, pp. 1–13 (2015)
Tomar, A., Muduli, L., Jana, P.K.: An efficient scheduling scheme for on-demand mobile charging in wireless rechargeable sensor networks. Pervasive Mob. Comput. 59, 101074 (2019)
Wang, C., Li, J., Ye, F., Yang, Y.: NETWRAP: an NDN based real-time wireless recharging framework for wireless sensor networks. IEEE Trans. Mobile Comput. 13(6), 1283–1297 (2014)
Wang, N., Wu, J., Dai, H.: Bundle charging: wireless charging energy minimization in dense wireless sensor networks. In: Proceedings of the 39th IEEE ICDCS, pp. 810–820 (2019)
Wei, Z., Li, M., Zhao, Q., Lyu, Z., Zhu, S., Wei, Z.: Multi-MC charging schedule algorithm with time windows in wireless rechargeable sensor networks. IEEE Access 7, 156217–156227 (2019)
Xie, L., Shi, Y., Hou, Y., Lou, W., Sherali, H., Midkiff, S.: On renewable sensor networks with wireless energy transfer: the multi-node case. In: Proceedings of the 9th IEEE SECON, pp. 10–18 (2012)
Xie, L., Shi, Y., Hou, Y.T., Lou, W., Sherali, H.D.: On traveling path and related problems for a mobile station in a rechargeable sensor network. In: Proceedings of the 13th ACM MobiHoc, pp. 109–118 (2013)
Xie, L., Shi, Y., Hou, Y.T., Lou, W., Sherali, H.D., Midkiff, S.F.: Bundling mobile base station and wireless energy transfer: modeling and optimization. In: Proceedings of IEEE INFOCOM, pp. 1636–1644 (2013)
Xu, W., Liang, W., Lin, X., Mao, G., Ren, X.: Towards perpetual sensor networks via deploying multiple mobile wireless chargers. In: Proceedings of the 43rd ICPP, pp. 80–89 (2014)
Zhou, P., Wang, C., Yang, Y.: Static and mobile target k-coverage in wireless rechargeable sensor networks. IEEE Trans. Mobile Comput. 18(10), 2430–2445 (2019)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Duan, X., Li, F., Yu, D., Yang, H., Sheng, H. (2020). Learning-Aided Mobile Charging for Rechargeable Sensor Networks. In: Yu, D., Dressler, F., Yu, J. (eds) Wireless Algorithms, Systems, and Applications. WASA 2020. Lecture Notes in Computer Science(), vol 12384. Springer, Cham. https://doi.org/10.1007/978-3-030-59016-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-59016-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-59015-4
Online ISBN: 978-3-030-59016-1
eBook Packages: Computer ScienceComputer Science (R0)