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Energy-Aware Algorithm for LoRa Technology: Prototype Implementation

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2020, ruSMART 2020)

Abstract

Internet of things (IoT) development has already become one of the main directions in the telecommunications and the information and communication system development as a whole. Promising solutions in the communication networks evolution, such as the latest LTE standards, concepts, and solutions for building 5G networks critical, include this component as an integral part of a promising communication network. There are various modern solutions for building IoT networks, and Long-Range Wide Area Network (LoRaWAN) is one of them. LoRaWAN is a technical solution for the physical and partially link network layers. The paper proposes an algorithm for ensuring traffic quality of service, latency, and data loss, as well as to provide an effective way of energy consumption. We impalement a prototype for Long Range (LoRa) based edge computing.

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References

  1. General Electric. What is edge computing? https://www.ge.com/digital/blog/what-edge-computing. Accessed 18 Apr 2019

  2. He, Y., Richard Yu, F., Zhao, N., Leung, V.C.M., Yin, H.: Software-defined networks with mobile edge computing and caching for smart cities: a big data deep reinforcement learning approach. IEEE Commun. Mag. 55(12), 31–37 (2017). https://doi.org/10.1109/MCOM.2017.1700246

    Article  Google Scholar 

  3. Khakimov, A., Muthanna, A., Muthanna, M.S.A.: Study of Fog computing structure. In: Proceedings of the 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), Moscow, Russia, 29 January–1 February 2018, pp. 51–54 (2018)

    Google Scholar 

  4. Perera, C., Qin, Y., Estrella, J.C., Reiff-Marganiec, S., Vasilakos, A.V.: Fog computing for sustainable smart cities: a survey. ACM Comput. Surv. 50(3) (2017). https://doi.org/10.1145/3057266

  5. Chen, L., et al.: A lora-based air quality monitor on unmanned aerial vehicle for smart city. In: 2018 International Conference on System Science and Engineering (ICSSE), pp. 1–5, June 2018

    Google Scholar 

  6. Taleb, T., Dutta, S., Ksentini, A., Iqbal, M., Flinck, H.: Mobile edge computing potential in making cities smarter. IEEE Commun. Mag. 55(3), 38–43 (2017). https://doi.org/10.1109/MCOM.2017.1600249CM

    Article  Google Scholar 

  7. Pyattaev, A., Johnsson, K., Surak, A., Florea, R., Andreev, S., Koucheryavy, Y.: Network-assisted D2D communications: implementing a technology prototype for cellular traffic offloading. In: IEEE Wireless Communications and Networking Conference, WCNC, art. no. 6953070, pp. 3266–3271 (2017)

    Google Scholar 

  8. Gia, T.N., Thanigaivelan, N.K., Rahmani, A.M., Westerlund, T., Liljeberg, P., Tenhunen, H.: Customizing 6LoWPAN networks towards Internet-of-Things based ubiquitous healthcare systems. In: NORCHIP 2014 - 32nd NORCHIP Conference: The Nordic Microelectronics Event. Institute of Electrical and Electronics Engineers Inc. (2014). https://doi.org/10.1109/NORCHIP.2014.7004716

  9. Nguyen Gia, T., et al.: Energy efficient wearable sensor node for IoT-based fall detection systems. Microprocess. Microsyst. 56, 34–46 (2018). https://doi.org/10.1016/j.micpro.2017.10.014

    Article  Google Scholar 

  10. Ometov, A., et al.: Toward trusted, social-aware D2D connectivity: bridging across the technology and sociality realms. IEEE Wireless Commun. 23(4), pp. 103–111 (2016). Art. no. 7553033

    Google Scholar 

  11. Muthanna, M.S.A., Wang, P., Wei, M., Ateya, A.A., Muthanna, A.: Toward an ultra-low latency and energy efficient LoRaWAN. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2019. LNCS, vol. 11660, pp. 233–242. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30859-9_20

    Chapter  Google Scholar 

  12. Dongare, A., et al.: Charm: exploiting geographical diversity through coherent combining in low-power wide-area networks. In: Proceedings of the International Conference on Information Processing in Sensor Networks, pp. 60–71 (2018)

    Google Scholar 

  13. Galinina, O., Tabassum, H., Mikhaylov, K., Andreev, S., Hossain, E., Koucheryavy, Y.: On feasibility of 5G-grade dedicated RF charging technology for wireless-powered wearables. IEEE Wirel. Commun. 23(2), pp. 28–37 (2016). Art. no. 7462482

    Google Scholar 

  14. Gerasimenko, M., Petrov, V., Galinina, O., Andreev, S., Koucheryavy, Y.: Energy and delay analysis of LTE-Advanced RACH performance under MTC overload. In: 2012 IEEE Globecom Workshops, GC Wkshps 2012, pp. 1632–1637 (2012). Art. no. 6477830

    Google Scholar 

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Acknowledgment

The publication has been prepared with the support of the “RUDN University Program 5-100” (recipient Abdukodir Khakimov). The reported study was funded by RFBR, project number 18-00-01555(18-00-01685) (recipient Konstantin Samouylov). For the research, infrastructure of the 5G Lab RUDN (Russia) was used.

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Correspondence to Abdukodir Khakimov .

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Khakimov, A., Muthanna, M.S.A., Mikhail, P., Ibodullokhodzha, I., Muthanna, A., Samouylov, K. (2020). Energy-Aware Algorithm for LoRa Technology: Prototype Implementation. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2020 2020. Lecture Notes in Computer Science(), vol 12525. Springer, Cham. https://doi.org/10.1007/978-3-030-65726-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-65726-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65725-3

  • Online ISBN: 978-3-030-65726-0

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