Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Telecommunication Systems
Erschienen in: Telecommunication Systems 2/2023

18.08.2023

Joint throughput-energy optimization in multi-gateway LoRaWAN networks

verfasst von: Ali Loubany, Samer Lahoud, Abed Ellatif Samhat, Melhem El Helou

Erschienen in: Telecommunication Systems | Ausgabe 2/2023

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Nowadays, LoRaWAN has become one of the most widely deployed low-power wide-area technologies suitable for Internet of Things applications. Sensor nodes powered by battery sources with a finite lifetime are the most common in these applications. Deploying a massive number of these nodes that send sporadic traffic increases collisions. In this paper, we propose a two-step algorithm in order to increase LoRaWAN network throughput, extend its lifetime, and therefore achieve high energy efficiency. First, we formulate a multi-objective optimization problem that jointly maximizes the network throughput and minimizes power consumption. Then, the power control step reduces the transmission power to the minimum allowed level, which preserves the reliability of communications. Our algorithm derives the optimal spreading factor and transmission power configuration for all nodes in LoRaWAN networks with multiple gateways. The results show that the proposed algorithm achieves higher energy efficiency compared to adaptive data rate (ADR) and other relevant state-of-the-art algorithms.
Vorheriger Artikel An efficient geometric octal zones distance estimation and attribute-based encryption for secure transfer of sensitive data

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
1
Computation time is evaluated on a 2.6 GHz Intel i7 computer with 16 GB of memory size.
 
Literatur
1.
Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H., & Zhao, W. (2017). A survey on internet of things: architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal, 4(5), 1125–1142.CrossRef
2.
Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. IEEE Internet of Things Journal, 1(1), 22–32.CrossRef
3.
Catherwood, P. A., Steele, D., Little, M., Mccomb, S., & Mclaughlin, J. (2018). A community-based iot personalized wireless healthcare solution trial. IEEE Journal of Translational Engineering in Health and Medicine, 6, 1–13.CrossRef
4.
Petäjäjärvi, J., Mikhaylov, K., Hämäläinen, M., & Iinatti, J. (2016)“Evaluation of lora lpwan technology for remote health and wellbeing monitoring,” in 2016 10th International Symposium on Medical Information and Communication Technology (ISMICT), pp. 1–5.
5.
Sartori, D., & Brunelli, D. (2016). A smart sensor for precision agriculture powered by microbial fuel cells. IEEE Sensors Applications Symposium (SAS), 2016, 1–6.
6.
Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: a survey. Computer Networks, 54(15), 2787–2805.CrossRef
7.
Raza, U., Kulkarni, P., & Sooriyabandara, M. (2017). Low power wide area networks: An overview. IEEE Communications Surveys Tutorials, 19(2), 855–873.CrossRef
8.
Mekkia, K., Bajica, E., Chaxela, F., & Meyerb, F. (2018). A comparative study of LPWAN technologies for large-scale IoT deployment, ICT express.
9.
Shanmuga Sundaram, J. P., Du, W., & Zhao, Z. (2020). A survey on lora networking: Research problems, current solutions, and open issues. IEEE Communications Surveys Tutorials, 22(1), 371–388.CrossRef
10.
11.
Haxhibeqiri, J., De Poorter, E., Moerman, I., & Hoebeke, J. (2018). A survey of lorawan for iot: From technology to application. Sensors, 18, 3995.CrossRef
12.
Casals Ibáñez, L., Mir Masnou, B., Vidal Ferré, R., & Gomez, C. (2017). Modeling the energy performance of lorawan. Sensors, 17, 2364.CrossRef
13.
Finnegan, J., Brown, S., & Farrell, R. (2018). Modeling the energy consumption of lorawan in ns-3 based on real world measurements. Global Information Infrastructure and Networking Symposium (GIIS), 2018, 1–4.
14.
15.
Alliance, L. (2017). LoRaWAN specification version 1.1. LoRa Alliance: Tech. Rep.
16.
Mikhaylov, K., Stusek, M., Masek, P., Fujdiak, R., Mozny, R., Andreev, S., & Hosek, J. (2020). On the performance of multi-gateway lorawan deployments: An experimental study. IEEE Wireless Communications and Networking Conference (WCNC), 2020, 1–6.
17.
Li, S., Raza, U., & Khan, A. (2018). How agile is the adaptive data rate mechanism of lorawan? IEEE Global Communications Conference (GLOBECOM), 2018, 206–212.
18.
Kufakunesu, R., Hancke, G., Abu-Mahfouz, A. (2020). A survey on adaptive data rate optimization in lorawan: Recent solutions and major challenges. Sensors (Basel, Switzerland), 20, 09.
19.
Dantas Silva, F. S., Neto, E. P., Oliveira, H., Rosário, D., Cerqueira, E., Both, C., Zeadally, S., & Neto, A. V. (2021). A survey on long-range wide-area network technology optimizations. IEEE Access, pp. 1–1.
20.
Georgiou, O., & Raza, U. (2017). Low power wide area network analysis: Can LoRa scale? IEEE Wireless Communications Letters, 6(2), 162–165.CrossRef
21.
Lim, J., & Han, Y. (2018). Spreading factor allocation for massive connectivity in lora systems. IEEE Communications Letters, 22(4), 800–803.CrossRef
22.
Caillouet, C., Heusse, M., & Rousseau, F. (2020). Bringing fairness in lorawan through sf allocation optimization. IEEE Symposium on Computers and Communications (ISCC), 2020, 1–6.
23.
Reynders, B., Meert, W., & Pollin, S. (2017). Power and spreading factor control in low power wide area networks. IEEE International Conference on Communications (ICC), 2017, 1–6.
24.
Tiurlikova, A., Stepanov, N., & Mikhaylov, K. (2018)“Method of assigning spreading factor to improve the scalability of the lorawan wide area network,” in 2018 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 1–4.
25.
Premsankar, G., Ghaddar, B., Slabicki, M., & Francesco, M. D. (2020). Optimal configuration of lora networks in smart cities. IEEE Transactions on Industrial Informatics, 16(12), 7243–7254.CrossRef
26.
27.
Reynders, B., Wang, Q., Tuset-Peiro, P., Vilajosana, X., & Pollin, S. (2018). Improving reliability and scalability of LoRaWANs through lightweight scheduling. IEEE Internet of Things Journal, 5(3), 1830–1842.CrossRef
28.
Lee, J., Jeong, W., & Choi, B. (2018). A scheduling algorithm for improving scalability of LoRaWAN. International Conference on Information and Communication Technology Convergence, Jul. pp. 1383–1388.
29.
Cuomo, F., Campo, M., Caponi, A., Bianchi, G., Rossini, G., & Pisani, P. (2017). EXPLoRa: Extending the performance of LoRa by suitable spreading factor allocations. 2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Oct., pp. 1–8.
30.
Georgiou, O., & Raza, U. (2017). Low power wide area network analysis: Can lora scale? IEEE Wireless Communications Letters, 6(2), 162–165.CrossRef
31.
Cuomo, F., Campo, M., Bassetti, E., Cartella, L., Sole, F, & Bianchi, G. (2018). Adaptive mitigation of the air-time pressure in lora multi-gateway architectures. European Wireless 2018; 24th European Wireless Conference, pp. 1–6.
32.
Sallum, E., Pereira, N., Alves, M., & Santos, M. (2020). Improving quality-of-service in lora low-power wide-area networks through optimized radio resource management. Journal of Sensor and Actuator Networks, 9, 10.CrossRef
33.
Slabicki, M., Premsankar, G., & Di Francesco, M. (2018). Adaptive configuration of lora networks for dense iot deployments. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, pp. 1–9.
34.
35.
Teymuri, B., Serati, R., Anagnostopoulos, N. A., & Rasti, M. (2023). Lp-mab: Improving the energy efficiency of lorawan using a reinforcement-learning-based adaptive configuration algorithm. Sensors, vol. 23, no. 4. [Online]. Available: https://​www.​mdpi.​com/​1424-8220/​23/​4/​2363
36.
37.
38.
Semtech, “SX1272/3/6/7/8: LoRa modem designer guide AN1200.13, rev.1,” Semtech, Tech. Rep., Jul 2013.
39.
LoRa Alliance Technical Committee Regional Parameters Workgroup. (2018). LoRaWAN 1.1 Regional Parameters. LoRa Alliance: Tech. Rep.
40.
Beltramelli, L., Mahmood, A. Österberg, P., & Gidlund, M. (2020). LoRa beyond ALOHA: An Investigation of Alternative Random Access Protocols. arXiv:​2002.​10732.
41.
Semtech, “SX1272/3 datasheet, rev. 4,” Semtech Corporation, Tech. Rep., Jan 2019.
42.
Adelantado, F., Vilajosana, X., Tuset-Peiro, P., Martinez, B., Melia-Segui, J., & Watteyne, T. (2017). Understanding the limits of lorawan. IEEE Communications Magazine, 55(9), 34–40.CrossRef
43.
Grodzevich, O., & Romanko, O. (2006). Normalization and other topics in multi-objective optimization. Proceedings of the Fields-MITACS Industrial Problems Workshop, pp. 89–101.
44.
Metadaten
Titel
Joint throughput-energy optimization in multi-gateway LoRaWAN networks
verfasst von
Ali Loubany
Samer Lahoud
Abed Ellatif Samhat
Melhem El Helou
Publikationsdatum
18.08.2023
Verlag
Springer US
Erschienen in
Telecommunication Systems / Ausgabe 2/2023
Print ISSN: 1018-4864
Elektronische ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-023-01048-8

Weitere Artikel der Ausgabe 2/2023

Telecommunication Systems 2/2023 Zur Ausgabe

OriginalPaper

An efficient geometric octal zones distance estimation and attribute-based encryption for secure transfer of sensitive data

OriginalPaper

Energy-aware mobile sink visiting nodes selection using a mean-shift clustering strategy for data accumulation in WSNs

OriginalPaper

Neural adaptive robust control for MEMS gyroscope with output constraints

OriginalPaper

Data dissemination protocol for VANETs to optimize the routing path using hybrid particle swarm optimization with sequential variable neighbourhood search

OriginalPaper

A fog-assisted privacy preserving scheme for vehicular LBS query

OriginalPaper

An energy efficient clustering with enhanced chicken swarm optimization algorithm with adaptive position routing protocol in mobile adhoc network

Neuer Inhalt

    Bildnachweise