Virtualization Approach for Machine-Type Communications in Multi-RAT Environment

  • Liljana Gavrilovska
  • Valentin Rakovic
  • Aleksandar Ichkov


Machine-type communications (MTC) represent a novel wireless communication paradigm that incorporates large number of devices and triggers several communication challenges. The MTC virtualization can overcome some of these challenges, provisioning decreased deployment costs, improved energy efficiency, improved coexistence with existing radio technologies, easy extensions of novel MTC technologies, etc. This paper discusses the virtualization approaches for MTC in a multi-RAT environment. The paper discusses the benefits and practical aspects of MTC virtualization, and evaluates the advantages and disadvantages of the Docker and OpenStack virtualization frameworks. The evaluation of both virtualization frameworks is conducted on a novel virtualized multi-RAT cloud-based demo platform that incorporates three distinct MTC technologies (SigFox, Z-Wave and LTE-M).


C-RAN MTC Virtualization Containerization Docker OpenStack 


  1. 1.
    Ozcelik, I. M., Korpeoglu, I., & Agrawala, A. (2017). Energy efficient IP-connectivity with IEEE 802.11 for home M2M networks. The Computer Journal, 60(6), 883–897.CrossRefGoogle Scholar
  2. 2.
    Lu, C. H., Wu, C. L., Weng, M. Y., Chen, W. C., & Fu, L. C. (2017). Context-aware energy saving system with multiple comfort-constrained optimization in M2M-based home environment. IEEE Transactions on Automation Science and Engineering, 14(3), 1400–1414.CrossRefGoogle Scholar
  3. 3.
    Rinne, J., Keskinen, J., Berger, P.R., Lupo, D., & Valkama, M. (2017). Wireless energy harvesting and communications: Limits and reliability. In 2017 IEEE wireless communications and networking conference workshops (WCNCW) (pp. 1–6).Google Scholar
  4. 4.
    Tuna, G., Kogias, D. G., Gungor, V. C., Gezer, C., Taskin, E., & Ayday, E. (2017). A survey on information security threats and solutions for machine to machine (M2M) communications. Journal of Parallel and Distributed Computing, 109(Supplement C), 142–154.CrossRefGoogle Scholar
  5. 5.
    Ghazvini, F. K., Mehmet-Ali, M., & Doughan, M. (2017). Scalable hybrid MAC protocol for M2M communications. Computer Networks, 127(Supplement C), 151–160.
  6. 6.
    Ramachandran, N., & Perumal, V. (2018). Delay-aware heterogeneous cluster-based data acquisition in internet of things. Computers and Electrical Engineering, 65, 44–58.CrossRefGoogle Scholar
  7. 7.
    Karkazis, P., Trakadas, P., Zahariadis, T., Chatzigiannakis, I., Dohler, M., Vitaletti, A., et al. (2015). Resource and service virtualisation in M2M and IoT platforms. International Journal of Intelligent Engineering Informatics, 3(2/3), 205–224.CrossRefGoogle Scholar
  8. 8.
    Khan, I., Belqasmi, F., Glitho, R., Crespi, N., Morrow, M., & Polakos, P. (2016). Wireless sensor network virtualization: A survey. IEEE Communications Surveys Tutorials, 18(1), 553–576.CrossRefGoogle Scholar
  9. 9.
    Kaiwartya, O., Abdullah, A. H., Cao, Y., Lloret, J., Kumar, S., Shah, R. R., et al. (2017). Virtualization in wireless sensor networks: Fault tolerant embedding for internet of things. IEEE Internet of Things Journal, PP(99), 1–1. Scholar
  10. 10.
    Ali, Z. H., Ali, H. A., & Badawy, M. M. (2017). A new proposed the internet of things (IoT) virtualization framework based on sensor-as-a-service concept. Wireless Personal Communications, 97, 1419–1443.CrossRefGoogle Scholar
  11. 11.
    Khazaei, H., Bannazadeh, H., & Leon-Garcia, A. (2017). End-to-end management of IoT applications. In 2017 IEEE conference on network softwarization (NetSoft) (pp. 1–3)Google Scholar
  12. 12.
    Li, M., Yu, F. R., Si, P., Sun, E., Zhang, Y., & Yao, H. (2016). Machine-to-machine (M2M) communications in software-defined and virtualized cellular networks. CoRR. arXiv:1611.08725.
  13. 13.
    Li, M., & Hu, S. (2017). Machine-to-machine (M2M) communications in virtualized cellular networks with MEC. CoRR. arXiv:1706.09107
  14. 14.
    Peng, M., Sun, Y., Li, X., Mao, Z., & Wang, C. (2016). Recent advances in cloud radio access networks: System architectures, key techniques, and open issues. IEEE Communications Surveys Tutorials, 18(3), 2282–2308.CrossRefGoogle Scholar
  15. 15.
    Checko, A. (2017). Cloud radio access network architecture: Towards 5G mobile networks. Ph.D. thesis. DTU Fotonik.
  16. 16.
    Online information.
  17. 17.
  18. 18.
  19. 19.
  20. 20.
  21. 21.
  22. 22.
  23. 23.
    Rakovic, V., Ichkov, A., Grosheva, N., Atanasovski, V., & Gavrilovska, L. (2017). Analysis of virtual resource allocation for cloud-ran based systems. In 2017 20th conference on innovations in clouds, internet and networks (ICIN) (pp. 60–64).Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Liljana Gavrilovska
    • 1
  • Valentin Rakovic
    • 1
  • Aleksandar Ichkov
    • 1
  1. 1.Faculty of Electrical Engineering and Information TechnologiesSs Cyril and Methodius University in SkopjeSkopjeMacedonia

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