Sub-GHz LPWAN Network Coexistence, Management and Virtualization: An Overview and Open Research Challenges

Abstract

The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. Low power wide area networks (LPWANs) fulfill these requirements by using sub-GHz radio frequencies (typically 433 or 868 MHz) with typical transmission ranges in the order of 1 up to 50 km. As a result, a single base station can cover large areas and can support high numbers of connected devices (>1000 per base station). Notorious initiatives in this domain are LoRa, Sigfox and the upcoming IEEE 802.11ah (or “HaLow”) standard. Although these new technologies have the potential to significantly impact many IoT deployments, the current market is very fragmented and many challenges exists related to deployment, scalability, management and coexistence aspects, making adoption of these technologies difficult for many companies. To remedy this, this paper proposes a conceptual framework to improve the performance of LPWAN networks through in-network optimization, cross-technology coexistence and cooperation and virtualization of management functions. In addition, the paper gives an overview of state of the art solutions and identifies open challenges for each of these aspects.

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References

  1. 1.

    (2015). LoRaWAN: What is it? A technical overview of LoRa and LoRaWAN, a technical overview of LoRa and LoRaWAN, LoRa Alliance Technical Marketing Workgroup 1.0.

  2. 2.

    WG802.11—Wireless LAN Working Group, 802.11ah-2016—IEEE Approved Draft Standard for Information Technology. https://standards.ieee.org/findstds/standard/802.11ah-2016.html. February 2017 release.

  3. 3.

    Park, M. (2015). IEEE 802.11ah: Sub-1-GHz license-exempt operation for the internet of things. IEEE Communication Magazine, 53(9), 145–151.

    Article  Google Scholar 

  4. 4.

    Tian, L., Famaey, J., & Latré, L. (2016). Evaluation of the IEEE 802.11ah restricted access window mechanism for dense IoT networks. In IEEE international symposium on a world of wireless, mobile and multimedia networks (WoWMoM).

  5. 5.

    Chang, K. H., & Mason, B. (2012). The IEEE 802.15.4g standard for smart metering utility networks. In 2012 IEEE third international conference on smart grid communications, Tainan (pp. 476–480).

  6. 6.

    Dujovne, D., Watteyne, T., Vilajosana, X., & Thubert, P. (2014). 6TiSCH: Deterministic IP-enabled industrial internet (of things). IEEE Communications Magazine, 52(12), 36–41.

    Article  Google Scholar 

  7. 7.

    Watteyne, T., Mehta, A., & Pister, K. (2009). Reliability through frequency diversity: Why channel hopping makes sense. In 6th ACM symposium on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks.

  8. 8.

    Shin, K., Park, I., Hong, J., Har, D., & Cho, D. (2015). Per-node throughput enhancement in Wi-Fi densenets. IEEE Communications Magazine, 53(1), 118–125.

    Article  Google Scholar 

  9. 9.

    Weyn, M. (2016). Low power wide area networks. Last accessed May 18, 2016, from https://sites.google.com/a/wesdec.be/mweyn/lpwan.

  10. 10.

    Daneels, G., Famaey, J., Bohez, S., Simoens, P., & Latré, S. (2015). Upstream content scheduling in Wi-Fi densenets during large-scale events. In IEEE globecom workshop on enabling technologies in future wireless local area networks (ETFWLAN).

  11. 11.

    Zats, S., Su, R., Watteyne, T., & Pister, K. S. J. (2011). Scalability of time synchronized wireless sensor networking. In 37th Annual conference of the IEEE Industrial Electronics Society (pp. 3011–3016).

  12. 12.

    Palattella, M. R., Accettura, N., Dohler, M., Grieco, L. A., & Boggia, G. (2012). Traffic aware scheduling algorithm for reliable low-power multi-hop IEEE 802.15.4e networks. In IEEE 23rd international symposium on personal, indoor and mobile radio communications - (PIMRC) (pp. 327–332). doi:10.1109/PIMRC.2012.6362805 

  13. 13.

    Dujovne, D., et al. (2014). 6TiSCH on-the-fly scheduling. Internet-Draft [work-in-progress], IETF Std., Rev. draft-dujovne-6tisch-on-the-fly-02, Feb 14, 2014.

  14. 14.

    Tian, L., Latré, L., & Famaey, J. (2016). Implementation and validation of an IEEE 802.11ah module for NS-3. In Workshop on ns-3 (WNS3).

  15. 15.

    Ogawa, K., Morikura, M., Yamamoto, K., & Sugihara, T. (2013). IEEE 802.11ah based M2M networks employing virtual grouping and power saving methods. IEICE Transactions on Communications, 96(12), 2976–2985.

    Article  Google Scholar 

  16. 16.

    Qutab-ud-din, M., Hazmi, A., Badihi, B., Larmo, A., Torsner, J., & Valkama, M. (2015). Performance analysis of IoT-enabling IEEE 802.11ah technology and its RAW mechanism with non-cross slot boundary holding schemes. In IEEE 16th international symposium on a world of wireless, mobile and multimedia networks (WoWMoM).

  17. 17.

    Park, M. (2014). IEEE 802.11ah: Energy efficient MAC protocols for long range wireless LAN. In IEEE international conference on communications (ICC) (pp. 2388–2393).

  18. 18.

    Park, C. W., Hwang, D., & Lee, T.-J. (2014). Enhancement of IEEE 802.11ah MAC for M2M communications. IEEE Communications Letters, 18(7), 1151–1154.

    Article  Google Scholar 

  19. 19.

    Lei, X., & Rhee, S. H. (2017). Wireless Personal Communications, 93, 933. doi:10.1007/s11277-017-3947-3.

    Article  Google Scholar 

  20. 20.

    Liang, C., & Yu, F. (2015). Wireless network virtualization: A survey, some research issues and challenges. IEEE Communications Surveys Tutorials, 17(1), 358–380.

    Article  Google Scholar 

  21. 21.

    Granelli, F., Gebremariam, A., Usman, M., Cugini, F., Stamati, V., Alitska, M., & Chatzimisios, P. (2015). Software defined and virtualized wireless access in future wireless networks: Scenarios and standards. IEEE Communications Magazine, 53(6), 26–34.

    Article  Google Scholar 

  22. 22.

    Yang, M., Jin, Y., Zeng, L., Wu, X., & Vasilakos, A. (2015). Software-defined and virtualized future mobile and wireless networks: A survey. Mobile Networks and Applications, 20(4–18), 2015.

    Google Scholar 

  23. 23.

    Paventhan, A., Krishna, H., Pahuja, N., Khan, M. F., & Jain, A. (2015). Experimental evaluation of IETF 6TiSCH in the context of smart grid. In IEEE 2nd world forum on internet of things (WF-IoT) (pp. 530–535).

  24. 24.

    Duquennoy, S., Al Nahas, B., Landsiedel, O., & Watteyne, T. (2015). Orchestra: Robust mesh networks through autonomously scheduled TSCH. In Proceedings of the 13th ACM conference on embedded networked sensor systems (pp. 337–350).

  25. 25.

    Liu, Y.-H., Huang, X., Vidojkovic, M., Ba, A., Harpe, P., Dolmans, G., & Groot, H. D. (2013). A 1.9 nJ/b 2.4 GHz multistandard (bluetooth low energy/zigbee/IEEE802.15.6) transceiver for personal/body-area networks. In ISSCC 2013.

  26. 26.

    Wong, A. C. W., Dawkins, M., Devita, G., Kasparidis, N., Katsiamis, A., King, O., et al. (2013). A 1 V 5 mA multimode IEEE 802.15.6/bluetooth low-energy WBAN transceiver for biotelemetry applications. IEEE Journal of Solid-State Circuits, 48(1), 186–198.

    Article  Google Scholar 

  27. 27.

    Fabbro, P. D., et al. (2010). A 0.8 V 2.4 GHz 1 Mb/s GFSK RF transceiver with on-chip DC–DC converter in a standard 0.18 µm CMOS technology. In Proceedings of ESSCIRC, Sept 14–16, 2010. doi:10.1109/ESSCIRC.2010.5619742.

  28. 28.

    Das, K., Mathews, E., Zand, P., Sanchez Ramirez, A., & Havinga, P. Efficient I/O joining and reliable data publication in energy harvested ISA100.11a network. In IEEE international conference on industrial technology (ICIT).

  29. 29.

    Yang, D., Xu, Y., & Gidlund, M. (2011). Wireless coexistence between IEEE 802.11- and IEEE 802.15.4-based networks: A survey. International Journal of Distributed Sensor Networks. doi:10.1155/2011/912152

    Google Scholar 

  30. 30.

    Challoo, R., Oladeinde, A., Yilmazer, N., Ozcelik, S., & Challoo, L. (2012). An overview and assessment of wireless technologies and coexistence of ZigBee, Bluetooth and Wi-Fi devices. Procedia Computer Science, 12, 386–391.

    Article  Google Scholar 

  31. 31.

    Pollin, S., Tan, I., Hodge, B., & Bahai, A. (2008). Harmful coexistence between 802.15.4 and 802.11: A measurement-based study. In 3rd international conference on cognitive radio oriented wireless networks and communications (CrownCom 2008) (pp. 1–6).

  32. 32.

    Lakshminarayanan, K., Sapra, S., Seshan, S., & Steenkiste, P. (2009). Rfdump: An architecture for monitoring the wireless ether. In Proceedings of the 5th ACM international conference on emerging networking experiments and technologies (CoNEXT).

  33. 33.

    Hermans, F., Larzon, L.-A., Rensfelt, O., & Gunningberg, P. (2012). A lightweight approach to online detection and classification of interference in 802.15.4-based sensor networks. In ACM SIGBED Review—Special Issue on the 3rd International Workshop on Networks of Cooperating Objects (CONET).

  34. 34.

    Zhou, R., Xiong, Y., Xing, G., Sun, L., & Ma, J. (2010). Zifi: Wireless LAN discovery via ZigBee interference signatures. In Proceedings of the sixteenth annual international conference on mobile computing and networking. MobiCom ‘10 (pp. 49–60). New York: ACM.

  35. 35.

    Rayanchu, S., Patro, A., & Banerjee, S. (2011). Airshark: Detecting non-WiFi RF devices using commodity WiFi hardware. In Proceedings of the ACM SIGCOMM conference on internet measurement conference. IMC ’11 ( pp. 137–154). New York: ACM.

  36. 36.

    Huang, J., Xing, G., Zhou, G., & Zhou, R. (2010). Beyond co-existence: Exploiting WiFi white space for Zigbee performance assurance. In 18th IEEE international conference on network protocols (pp. 305–314).

  37. 37.

    Javed, Q., & Prakash, R. (2013). CHAMELEON: A framework for coexistence of wireless technologies in an unlicensed band. Wireless Personal Communications, 77(1), 777–808.

    Article  Google Scholar 

  38. 38.

    Tytgat, L., Yaron, O., Pollin, S., Moerman, I., & Demeester, P. (2015). Analysis and experimental verification of frequency-based interference avoidance mechanisms in IEEE 802.15.4. IEEE/ACM Transactions on Networking, 23(2), 369–382.

    Article  Google Scholar 

  39. 39.

    Correia, L. H. A., Tran, T.-D., Pereira, V. N. S. S., Giacomin, J. C., & Sá Silva, J. M. (2015). DynMAC: A resistant MAC protocol to coexistence in wireless sensor networks. Computer Networks, 76, 1–16.

    Article  Google Scholar 

  40. 40.

    Hayashi, H. (2015). Standardization of wireless coexistence in industrial automation. In 2015 54th Annual conference of the Society of Instrument and Control Engineers of Japan (SICE) (pp. 968–973).

  41. 41.

    Chiwewe, T. M., Mbuya, C. F., & Hancke, G. P. (2015). Using cognitive radio for interference-resistant industrial wireless sensor networks: An overview. IEEE Transactions on Industrial Informatics, 11(6), 1466–1481.

    Article  Google Scholar 

  42. 42.

    De Valck, P., Moerman, I., Croce, D., Giuliano, F., Tinnirello, I., Garlisi, D., De Poorter, E., & Jooris, B. (2014). Exploiting programmable architectures for WiFi/ZigBee inter-technology cooperation. EURASIP Journal on Wireless Communications and Networking, 2014, 212.

    Article  Google Scholar 

  43. 43.

    Chebrolu, K., & Dhekne, A. (2009). Esense: Communication through energy sensing. In Proceedings of the 15th annual international conference on mobile computing and networking (MobiCom ‘09) (pp. 85–96). New York, NY: ACM.

  44. 44.

    Fischer, A., Botero, J., Till Beck, M., de Meer, H., & Hesselbach, X. (2013). Virtual network embedding: A survey. IEEE Communications Surveys & Tutorials, 15(4).

  45. 45.

    Lin, T., Bannazadeh, H., & Leon-Garcia, A. (2015). Introducing wireless access programmability using software-defined infrastructure. In IFIP/IEEE international symposium on integrated network management (IM) (pp. 585–591).

  46. 46.

    Guo, K., Sanadhya, S., & Woo, T. (2015). Vifi: Virtualizing WLAN using commodity hardware. ACM SIGMOBILE Mobile Computing and Communications Review, 18(3), 41–48.

    Article  Google Scholar 

  47. 47.

    Pelov, A., Toutain, L., & Delibie, Y. (2016). Constrained signaling over LP-WAN. Internet Engineering Task Force draft. https://tools.ietf.org/html/draft-pelov-core-cosol-01. Feb 17, 2016.

  48. 48.

    Van den Abeele, F., Hoebeke, J., Moerman, I., & Demeester, P. (2014). Fine-grained management of CoAP interactions with constrained IoT devices. In IEEE/IFIP network operations and management symposium, proceedings (pp. 1–5).

  49. 49.

    Bonomi, F., et al. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on mobile cloud computing (pp. 13–16). Helsinki: ACM.

  50. 50.

    Hu, Y. C., Patel, M., Sabella, D., Sprecher, N., & Young, V. (2015). Mobile edge computing—A key technology towards 5G. ETSI White Paper (11).

  51. 51.

    Baldo, N., Tamma, B. R., Manoj, B., Rao, R., & Zorzi, M. (2009). A neural network based cognitive controller for dynamic channel selection. In IEEE international conference on communications, 2009. ICC’09 (pp. 1–5). IEEE.

  52. 52.

    Zorzi, M., Zanella, A., Testolin, A., De Filippo De Grazia, M., & Zorzi, M. (2015). Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence. IEEE Access, 3, 1512–1530.

    Article  Google Scholar 

  53. 53.

    Kulin, M., Fortuna, C., De Poorter, E., Deschrijver, D., & Moerman, I. (2016). Data-driven design of intelligent wireless networks: An overview and tutorial. Sensors Journal, 16(6), 790.

    Article  Google Scholar 

  54. 54.

    Compton, R., Mehari, M. T., Colbourn, C. J., De Poorter, E., & Syrotiuk, V. R. (2016). Screening interacting factors in a wireless network testbed using locating arrays. In The international workshop on computer and networking experimental research, IEEE conference on computer communications workshops (INFOCOM WKSHPS).

  55. 55.

    Munawar, W., Alizai, M. H., Landsiedel, O., & Wehrle, K. (2010). Dynamic TinyOS: Modular and transparent incremental code-updates for sensor networks. In IEEE ICC 2010, May 23–27.

  56. 56.

    Marrón, P. J., Gauger, M., Lachenmann, A., Minder, D., Saukh, O., & Rothermel, K. (2006). FlexCup: A flexible and efficient code update mechanism for sensor networks. In EWSN 2006, Feb 13–15.

  57. 57.

    Ruckebusch, P., De Poorter, E., Fortuna, C., & Moerman, I. (2016). GITAR: Generic extension for Internet-of-Things architectures enabling dynamic updates of network and application modules. Ad Hoc Networks, 36(P1), 127–151.

    Article  Google Scholar 

  58. 58.

    Ishaq, I., Hoebeke, J., Moerman, I., & Demeester, P. (2016). Observing CoAP groups efficiently. Ad Hoc Networks, 37(part 2), 368–388.

    Article  Google Scholar 

  59. 59.

    Ishaq, I., Hoebeke, J., Van den Abeele, F., Rossey, J., Moerman, I., & Demeester, P. (2014). Flexible unicast-based group communication for CoAP-enabled devices. Sensors, 14(60), 9833–9877.

    Article  Google Scholar 

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Acknowledgements

This work was carried out in the context of following projects. IDEAL-IoT (Intelligent DEnse And Longe range IoT networks) is an SBO project funded by the Fund for Scientific Research-Flanders (FWO-V) under Grant Agreement #S004017N. ‘Processing visual sensor data in low-power wide area networks’ is a project funded by the Fund for Scientific Research-Flanders (FWO-V) under Grant Agreement #G084177N. The UGent GOA “Disposable and biodegradable wireless networks for extreme conditions” project. The H2020 eWINE project under Grant Agreement Number 688116.

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Correspondence to Eli De Poorter.

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De Poorter, E., Hoebeke, J., Strobbe, M. et al. Sub-GHz LPWAN Network Coexistence, Management and Virtualization: An Overview and Open Research Challenges. Wireless Pers Commun 95, 187–213 (2017). https://doi.org/10.1007/s11277-017-4419-5

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Keywords

  • Sub-GHz networks
  • LPWAN
  • LoRa
  • SigFox
  • IEEE 802.11ah
  • DASH7
  • Coexistence
  • Network management
  • Virtualization
  • Scalability
  • QoS
  • Energy efficiency