Wireless Personal Communications

, Volume 103, Issue 3, pp 2137–2154 | Cite as

Energy and Latency-Aware Scheduling Under Channel Uncertainties in LTE Networks for Massive IoT

  • Mohammad Reza Mardani
  • Salman MohebiEmail author
  • Mohammad Ghanbari


The machine-to-machine (M2M) communication is an enabler technology for internet of things (IoT) that provides communication between machines and devices without human intervention. One of the main challenges in IoT is managing a large number of machine-type communications co-existing with the human to human (H2H) or human type communications. Long term evolution (LTE) and LTE-advanced (LTE-A) technologies due to their inherent characteristics like high capacity and flexibility in data access management are appropriate choices for M2M/IoT systems. In this paper, a two-phase intelligent scheduling mechanism based on interval type-2 fuzzy logic to (1) satisfy QoS requirements, (2) ensure fair resource allocation and (3) control energy level of devices for coexistence of M2M/H2H traffics in LTE-A networks, is presented. The proposed interval type-2 fuzzy Logic mechanism enhances data traffic efficiency by predicting and handling the network uncertainties. The performance of the proposed algorithm is evaluated in terms of various metrics such as delay, throughput, and bandwidth utilization.


M2M communication LTE network Resource allocation Internet of things Fuzzy logic 



  1. 1.
    Aijaz, A., Tshangini, M., Nakhai, M. R., Chu, X., & Aghvami, A.-H. (2014). Energy-efficient uplink resource allocation in LTE networks with M2M/H2H co-existence under statistical QoS guarantees. IEEE Transactions on Communications, 62(7), 2353–2365.CrossRefGoogle Scholar
  2. 2.
    Berardinelli, G., De Temino, L. Á. M. R., Frattasi, S., Rahman, M. I., & Mogensen, P. (2008). OFDMA vs. SC-FDMA: Performance comparison in local area IMT-A scenarios. IEEE Wireless Communications, 15(5), 64–72.CrossRefGoogle Scholar
  3. 3.
    Rajpal, J. (2017). Framework for enabling machine-type communication services. IET Wireless Sensor Systems, 7(1), 9–14.CrossRefGoogle Scholar
  4. 4.
    Chen, S., Ma, R., Chen, H.-H., Zhang, H., Meng, W., & Liu, J. (2017). Machine-to-machine communications in ultra-dense networks—A survey. IEEE Communications Surveys and Tutorials, 19, 1478–1503.CrossRefGoogle Scholar
  5. 5.
    Gazis, V. (2017). A survey of standards for machine-to-machine and the internet of things. IEEE Communications Surveys & Tutorials, 19(1), 482–511.CrossRefGoogle Scholar
  6. 6.
    Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.CrossRefGoogle Scholar
  7. 7.
    Chen, M., Wan, J., & Li, F. (2012). Machine-to-machine communications. KSII Transactions on Internet and Information Systems (TIIS), 6(2), 480–497.Google Scholar
  8. 8.
    Botta, A., de Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.CrossRefGoogle Scholar
  9. 9.
    Antipolis, S. (2006). 3rd Generation Partnership Project (3GPP). Physical layer aspects for evolved UTRA (release 7).Google Scholar
  10. 10.
    Antipolis, S. (2010). 3rd Generation Partnership Project (3GPP). Service requirements for machine type communications.Google Scholar
  11. 11.
    Mehaseb, M. A., Gadallah, Y., Elhamy, A., & Elhennawy, H. (2016). Classification of LTE uplink scheduling techniques: An M2M perspective. IEEE Communications Surveys & Tutorials, 18(2), 1310–1335.CrossRefGoogle Scholar
  12. 12.
    Abu-Ali, N., Taha, A.-E. M., Salah, M., & Hassanein, H. (2014). Uplink scheduling in LTE and LTE-advanced: Tutorial, survey and evaluation framework. IEEE Communications Surveys & Tutorials, 16(3), 1239–1265.CrossRefGoogle Scholar
  13. 13.
    Maia, A. M., Vieira, D., de Castro, M. F., & Ghamri-Doudane, Y. (2014). Comparative performance study of LTE uplink schedulers for M2M communication. In Wireless days (WD), 2014 IFIP (pp. 1–4). IEEE.Google Scholar
  14. 14.
    Abdalla, I., & Venkatesan, S. (2013). A QoE preserving M2M-aware hybrid scheduler for LTE uplink. In 2013 international conference on selected topics in mobile and wireless networking (MoWNeT) (pp. 127–132). IEEE.Google Scholar
  15. 15.
    Maia, A. M., de Castro, M. F., & Vieira, D. (2014). A dynamic LTE uplink packet scheduler for machine-to-machine communication. In 2014 IEEE 25th annual international symposium on personal, indoor, and mobile radio communication (PIMRC) (pp. 1609–1614). IEEE.Google Scholar
  16. 16.
    Chen, B., Fan, Z., Cao, F., Oikonomou, G., & Tryfonas, T. (2015). Class based overall priority scheduling for M2M communications over LTE networks. In 2015 IEEE 81st vehicular technology conference (VTC Spring) (pp. 1–5). IEEE.Google Scholar
  17. 17.
    Li, N., Cao, C., & Wang, C. (2017). Dynamic resource allocation and access class barring scheme for delay-sensitive devices in machine to machin (M2M) communnications. Sensors, 17(6), 1407.CrossRefGoogle Scholar
  18. 18.
    Giluka, M. K., Rajoria, N., Kulkarni, A. C., Sathya, V., & Tamma, B. R. (2014) Class based dynamic priority scheduling for uplink to support M2M communications in LTE. In 2014 IEEE world forum on internet of things (WF-IoT) (pp. 313–317). IEEE.Google Scholar
  19. 19.
    Giluka, M. K., Kumar, N. S., Rajoria, N., Tamma, B. R. (2014). Class based priority scheduling to support machine to machine communications in LTE systems. In 2014 20th national conference on communications (NCC) (pp. 1–6). IEEE.Google Scholar
  20. 20.
    Zhenqi, S., Haifeng, Y., Xuefen, C., & Hongxia, L. (2013). Research on uplink scheduling algorithm of massive M2M and H2H services in LTE. In 2013 IET International Conference on Information and Communications Technologies (IETICT) (pp. 365–369)Google Scholar
  21. 21.
    Jaheon, G., Yoon, H.-W., Lee, J., Bae, S. J., & Chung, M. Y. (2015). A resource allocation scheme for device-to-device communications using LTE-A uplink resources. Pervasive and Mobile Computing, 18, 104–117.CrossRefGoogle Scholar
  22. 22.
    Kaddour, F. Z., Vivier, E., Mroueh, L., Pischella, M., & Martins, P. (2015). Green opportunistic and efficient resource block allocation algorithm for LTE uplink networks. IEEE Transactions on Vehicular Technology, 64(10), 4537–4550.CrossRefGoogle Scholar
  23. 23.
    Xiang, X., Lin, C., Chen, X., & Shen, X. (2015). Toward optimal admission control and resource allocation for LTE-A femtocell uplink. IEEE Transactions on Vehicular Technology, 64(7), 3247–3261.Google Scholar
  24. 24.
    Yang, K., Martin, S., & Yahiya, T. A. (2015). Lte uplink interference aware resource allocation. Computer Communications, 66, 45–53.CrossRefGoogle Scholar
  25. 25.
    AlQahtani, S. A. (2017). Analysis and modelling of power consumption-aware priority-based scheduling for M2M data aggregation over long-term-evolution networks. IET Communications, 11(2), 177–184.CrossRefGoogle Scholar
  26. 26.
    Azari, A., & Miao, G. (2015). Lifetime-aware scheduling and power control for M2M communications in LTE networks. In VTC. 11–14 May 2015 (p. 2015). Scotland: Glasgow.Google Scholar
  27. 27.
    Zhang, X., Shen, X. S., & Xie, L.-L. (2016). Uplink achievable rate and power allocation in cooperative LTE-advanced networks. IEEE Transactions on Vehicular Technology, 65(4), 2196–2207.CrossRefGoogle Scholar
  28. 28.
    Chen, J.-J., Liang, J.-M., & Chen, Z.-Y. (2014). Energy-efficient uplink radio resource management in LTE-advanced relay networks for internet of things. In 2014 international wireless communications and mobile computing conference (IWCMC) (pp. 745–750). IEEE.Google Scholar
  29. 29.
    Tian, H., Xie, W., Gan, X., & Youyun, X. (2016). Hybrid user association for maximising energy efficiency in heterogeneous networks with human-to-human/machine-to-machine coexistence. IET Communications, 10(9), 1035–1043.CrossRefGoogle Scholar
  30. 30.
    Aijaz, A., & Aghvami, H. (2013). On radio resource allocation in lte networks with machine-to-machine communications. In 2013 IEEE 77th vehicular technology conference (VTC Spring) (pp. 1–5). IEEE.Google Scholar
  31. 31.
    Hasan, M., Hossain, E., & Niyato, D. (2013). Random access for machine-to-machine communication in LTE-advanced networks: Issues and approaches. IEEE Communications Magazine, 51(6), 86–93.CrossRefGoogle Scholar
  32. 32.
    Taleb, T., & Kunz, A. (2012). Machine type communications in 3GPP networks: Potential, challenges, and solutions. IEEE Communications Magazine, 50(3), 178–184.CrossRefGoogle Scholar
  33. 33.
    Ghavimi, F., & Chen, H.-H. (2014). M2M communications in 3GPP LTE/LTE-a networks: Architectures, service requirements, challenges and applications. IEEE Communications Surveys and Tutorials, 17(2), 525–549.CrossRefGoogle Scholar
  34. 34.
    Yaacoub, E., & Dawy, Z. (2012). A survey on uplink resource allocation in OFDMA wireless networks. IEEE Communications Surveys & Tutorials, 14(2), 322–337.CrossRefGoogle Scholar
  35. 35.
    Boccardi, F., Heath, R. W., Lozano, A., Marzetta, T. L., & Popovski, P. (2014). Five disruptive technology directions for 5G. IEEE Communications Magazine, 52(2), 74–80.CrossRefGoogle Scholar
  36. 36.
    Karnik, N. N., Mendel, J. M., & Liang, Q. (1999). Type-2 fuzzy logic systems. EEE Transactions on Fuzzy Systems, 7(6), 643–658.CrossRefGoogle Scholar
  37. 37.
    Wu, D. (2010). A brief tutorial on interval type-2 fuzzy sets and systems. Fuzzy sets and systems.Google Scholar
  38. 38.
    Liu, R., Wu, W., Zhu, H., & Yang, D. (2011). M2M-oriented QoS categorization in cellular network. In 2011 7th international conference on wireless communications, networking and mobile computing (WiCOM) (pp. 1–5). IEEE.Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.School of ECE, College of EngineeringUniversity of TehranTehranIran
  2. 2.Faculty of New Sciences and TechnologiesUniversity of TehranTehranIran
  3. 3.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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