Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  3. Rajpal, J. (2017). Framework for enabling machine-type communication services. IET Wireless Sensor Systems, 7(1), 9–14.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. 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.

    Article  Google Scholar 

  9. Antipolis, S. (2006). 3rd Generation Partnership Project (3GPP). Physical layer aspects for evolved UTRA (release 7).

  10. Antipolis, S. (2010). 3rd Generation Partnership Project (3GPP). Service requirements for machine type communications.

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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.

  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.

  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.

  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.

    Article  Google Scholar 

  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.

  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.

  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)

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. Yang, K., Martin, S., & Yahiya, T. A. (2015). Lte uplink interference aware resource allocation. Computer Communications, 66, 45–53.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  32. Taleb, T., & Kunz, A. (2012). Machine type communications in 3GPP networks: Potential, challenges, and solutions. IEEE Communications Magazine, 50(3), 178–184.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  34. Yaacoub, E., & Dawy, Z. (2012). A survey on uplink resource allocation in OFDMA wireless networks. IEEE Communications Surveys & Tutorials, 14(2), 322–337.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  36. Karnik, N. N., Mendel, J. M., & Liang, Q. (1999). Type-2 fuzzy logic systems. EEE Transactions on Fuzzy Systems, 7(6), 643–658.

    Article  Google Scholar 

  37. Wu, D. (2010). A brief tutorial on interval type-2 fuzzy sets and systems. Fuzzy sets and systems.

  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.

Download references

Author information

Authors and Affiliations

  1. School of ECE, College of Engineering, University of Tehran, Tehran, Iran

    Mohammad Reza Mardani & Mohammad Ghanbari

  2. Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran

    Salman Mohebi

  3. School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK

    Mohammad Ghanbari

Authors
  1. Mohammad Reza Mardani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Salman Mohebi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Ghanbari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Salman Mohebi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mardani, M.R., Mohebi, S. & Ghanbari, M. Energy and Latency-Aware Scheduling Under Channel Uncertainties in LTE Networks for Massive IoT. Wireless Pers Commun 103, 2137–2154 (2018). https://doi.org/10.1007/s11277-018-5901-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5901-4

Keywords

Search

Navigation