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Interference Aware Heuristics to Optimize Power Beacons for Battery-less WSNs

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Published:24 October 2022Publication History

ABSTRACT

To achieve an infinite lifetime of sensing infrastructure in Internet-of-Things, battery-less wireless powered sensor networks (WPSNs) are an important step. The nodes in battery-less WPSNs harvest and store energy in super-capacitors from RF signal which are periodically transmitted by power beacons (PBs) or chargers. However, using multiple power chargers requires a focus on a crucial problem of interference. The sensor nodes which are covered by more than one power beacons become unreliable because of the overlapping signals from chargers since the overlap can be constructive or destructive. In this paper, we propose an algorithm to optimize the number and placement of power beacons such that interference can be reduced. The result shows that our proposed optimal power beacon location (OPBL) algorithm reduces interference in 60% of cases and also reduces data transmission time (DTT) by 30% in 24% of cases in comparison to the state-of-the-art.

References

  1. 2020. P2110b Module Datasheet. https://www.powercastco.com/documentation/p2110b-module-datasheet/Google ScholarGoogle Scholar
  2. Therese Biedl, Ahmad Biniaz, and Anna Lubiw. 2021. Minimum ply covering of points with disks and squares. Computational Geometry 94 (2021), 101712.Google ScholarGoogle ScholarCross RefCross Ref
  3. Ahmad Biniaz and Zhikai Lin. 2020. Minimum Ply Covering of Points with Convex Shapes. In CCCG. 2--5.Google ScholarGoogle Scholar
  4. Rémi Dekimpe, Pengcheng Xu, Maxime Schramme, Denis Flandre, and David Bol. 2018. Abattery-less BLE IoT motion detector supplied by 2.45-GHz wireless power transfer. In 2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS). IEEE, 68--75.Google ScholarGoogle Scholar
  5. Carmen Delgado and Jeroen Famaey. 2021. Optimal energy-aware task scheduling for batteryless IoT devices. IEEE Transactions on Emerging Topics in Computing (2021).Google ScholarGoogle ScholarCross RefCross Ref
  6. Carmen Delgado, José María Sanz, Chris Blondia, and Jeroen Famaey. 2020. Batteryless LoRaWAN communications using energy harvesting: Modeling and characterization. IEEE Internet of Things Journal 8, 4 (2020), 2694--2711.Google ScholarGoogle ScholarCross RefCross Ref
  7. Amit Kumar Dhar, Raghunath Reddy Madireddy, Supantha Pandit, and Jagpreet Singh. 2019. Maximum independent and disjoint coverage. In International Conference on Theory and Applications of Models of Computation. Springer, 134-- 153.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Shivani Dhok, Prasanna Raut, Prabhat Kumar Sharma, Keshav Singh, and Chih- Peng Li. 2021. Non-Linear Energy Harvesting in RIS-assisted URLLC Networks for Industry Automation. IEEE Transactions on Communications 69, 11 (2021), 7761--7774.Google ScholarGoogle ScholarCross RefCross Ref
  9. Aurelien Du Pasquier, Irene Plitz, Serafin Menocal, and Glenn Amatucci. 2003. A comparative study of Li-ion battery, supercapacitor and nonaqueous asymmetric hybrid devices for automotive applications. Journal of power sources 115, 1 (2003), 171--178.Google ScholarGoogle ScholarCross RefCross Ref
  10. Peng Guo, Xuefeng Liu, Shaojie Tang, and Jiannong Cao. 2016. Concurrently wireless charging sensor networks with efficient scheduling. IEEE Transactions on Mobile Computing 16, 9 (2016), 2450--2463.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Mike Hayes and Brian Zahnstecher. 2021. The Virtuous Circle of 5G, IoT and Energy Harvesting. IEEE Power Electronics Magazine 8, 3 (2021), 22--29.Google ScholarGoogle ScholarCross RefCross Ref
  12. Shifei Huang, Xianglin Zhu, Samrat Sarkar, and Yufeng Zhao. 2019. Challenges and opportunities for supercapacitors. APL Materials 7, 10 (2019), 100901.Google ScholarGoogle ScholarCross RefCross Ref
  13. Arpita Jaitawat and Arun Kumar Singh. 2020. Battery and supercapacitor imperfections modeling and comparison for RF energy harvesting wireless sensor network. Wireless Networks 26, 2 (2020), 843--853.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Akash Kumar and Jagpreet Singh. 2021. Optimization of Substrate Layer Material and Its Mechanical Properties for Piezoelectric Cantilever Energy Harvesting System. Advanced Theory and Simulations 4, 8 (2021), 2100156.Google ScholarGoogle ScholarCross RefCross Ref
  15. Saeed Mehrabi. 2016. Unique Set Cover on Unit Disks and Unit Squares. arXiv preprint arXiv:1607.07378 (2016).Google ScholarGoogle Scholar
  16. M Yousof Naderi, Kaushik R Chowdhury, and Stefano Basagni. 2015. Wireless sensor networks with RF energy harvesting: Energy models and analysis. In 2015 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 1494--1499.Google ScholarGoogle ScholarCross RefCross Ref
  17. Subhas C Nandy, Supantha Pandit, and Sasanka Roy. 2017. Covering Points: Minimizing the Maximum Depth. In CCCG. 37--42.Google ScholarGoogle Scholar
  18. Lingfeng Shao, Junjie Yang, and Jicheng Fang. 2020. A Distributed Optimization Algorithm for Energy of Wireless Sensor Networks Based on Potential Game. International Journal of Photoenergy 2020 (2020).Google ScholarGoogle ScholarCross RefCross Ref
  19. Sukhwinder Singh Sran, Jagpreet Singh, and Lakhwinder Kaur. 2018. Structure free aggregation in duty cycle sensor networks for delay sensitive applications. IEEE Transactions on Green Communications and Networking 2, 4 (2018), 1140-- 1149.Google ScholarGoogle ScholarCross RefCross Ref
  20. Mehmet Erkan Yüksel. 2019. Design and implementation of A batteryless wireless embedded system for IoT applications. Electrica 19, 1 (2019), 1--11.Google ScholarGoogle ScholarCross RefCross Ref
  21. Dimitrios Zorbas, Patrice Raveneau, Yacine Ghamri-Doudane, and Christos Douligeris. 2017. On the optimal number of chargers in battery-less wirelessly powered sensor networks. In 2017 IEEE Symposium on Computers and Communications (ISCC). IEEE, 1312--1317.Google ScholarGoogle ScholarCross RefCross Ref

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            cover image ACM Conferences
            MSWiM '22: Proceedings of the 25th International ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems
            October 2022
            243 pages
            ISBN:9781450394826
            DOI:10.1145/3551659

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            Publication History

            • Published: 24 October 2022

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            MSWiM '22 Paper Acceptance Rate27of117submissions,23%Overall Acceptance Rate398of1,577submissions,25%
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