Supporting QoS requirements provisions on 5G network slices using an efficient priority-based polling technique

  • Salman Ali AlQahtaniEmail author
  • Abdulaziz Saud Altamrah


Mobile operators aim to enhance the Quality of Service (QoS) in each new mobile network generation. The upcoming 5G mobile network is expected to make a revolutionary enhancement in the provided service level. Serving diverse requirements from different mobile network users in a flexible and a dynamic way is a key demand. Thus, the 5G network-slicing concept provides an optimal and an efficient way to deal with the diversity of end users requirements and demands. In 5G, three different network slices share the network resources in a virtually isolated slicing manner. These slices will be in different priority classes. Indeed, priority scheduling algorithms are needed to guarantee the service level for each slice among all other lesser priority slices. This paper proposes a priority-based polling scheme with multiple scheduling techniques for the data traffic coming from multiple 5G network slices. Cyclic and random polling with/without priority are analyzed and discussed for multiple 5G use cases. The analytical model of the proposed priority-based polling scheme is presented and the performance measures in terms of the average waiting time and utilization are derived. The results prove that the proposed polling scheme shows a powerful ability to control the 5G virtual base-band units pool and guard the QoS of the 5G slices, which is what 5G networks need.


Network slicing Polling discipline QoS Priority Scheduling 5G 



This work was supported by the Research Center of College of Computer and Information Sciences, King Saud University. The authors are grateful for this support.


  1. 1.
    da Silva, I., Mildh, G., Kaloxylos, A., Spapis, P., Buracchini, E., Trogolo, A., et al. (2016). Impact of network slicing on 5G radio access networks. In 2016 European conference on networks and communications (EuCNC) (pp. 153–157).Google Scholar
  2. 2.
    Zhang, H., Liu, N., Chu, X., Long, K., Aghvami, A.-H., & Leung, V. C. (2017). Network slicing based 5G and future mobile networks: Mobility, resource management, and challenges. IEEE Communications Magazine, 55, 138–145.CrossRefGoogle Scholar
  3. 3.
    Ordonez-Lucena, J., Ameigeiras, P., Lopez, D., Ramos-Munoz, J. J., Lorca, J., & Folgueira, J. (2017). Network slicing for 5G with SDN/NFV: Concepts, architectures, and challenges. IEEE Communications Magazine, 55, 80–87.CrossRefGoogle Scholar
  4. 4.
    Akyildiz, I. F., Nie, S., Lin, S.-C., & Chandrasekaran, M. (2016). 5G roadmap: 10 key enabling technologies. Computer Networks, 106, 17–48.CrossRefGoogle Scholar
  5. 5.
    Choi, Y.-I., & Park, N. (2017). Slice architecture for 5G core network. In 2017 Ninth international conference on ubiquitous and future networks (ICUFN) (pp. 571–575).Google Scholar
  6. 6.
    Richart, M., Baliosian, J., Serrat, J., & Gorricho, J.-L. (2016). Resource slicing in virtual wireless networks: A survey. IEEE Transactions on Network and Service Management, 13(3), 462–476.CrossRefGoogle Scholar
  7. 7.
    Dighriri, M., Alfoudi, A. S. D., Lee, G. M., Baker, T., & Pereira, R. (2017). Comparison data traffic scheduling techniques for classifying QoS over 5G mobile networks. In 2017 31st International conference on advanced information networking and applications workshops (WAINA) (pp. 492–497).Google Scholar
  8. 8.
    Ghavimi, F., & Chen, H.-H. (2015). M2M communications in 3GPP LTE/LTE-A networks: Architectures, service requirements, challenges, and applications. IEEE Communications Surveys & Tutorials, 17, 525–549.CrossRefGoogle Scholar
  9. 9.
    Foukas, X., Patounas, G., Elmokashfi, A., & Marina, M. K. (2017). Network slicing in 5G: Survey and challenges. IEEE Communications Magazine, 55, 94–100.CrossRefGoogle Scholar
  10. 10.
    Kotulski, Z., Nowak, T., Sepczuk, M., Tunia, M., Artych, R., Bocianiak, K., et al. (2017). On end-to-end approach for slice isolation in 5G networks. Fundamental challenges. In 2017 Federated conference on computer science and information systems (FedCSIS) (pp. 783–792).Google Scholar
  11. 11.
    Gong, J., Ge, L., Su, X., & Zeng, J. (2017). Radio access network slicing in 5G. In World conference on information systems and technologies (pp. 207–210).Google Scholar
  12. 12.
    Yu, H., Lee, H., & Jeon, H. (2017). What is 5G? Emerging 5G mobile services and network requirements. Sustainability, 9, 1848.CrossRefGoogle Scholar
  13. 13.
    Mohsen, N., & Hassan, K. S. (2015). C-RAN simulator: A tool for evaluating 5G cloud-based networks system-level performance. In 2015 IEEE 11th International conference on wireless and mobile computing, networking and communications (WiMob) (pp. 302–309).Google Scholar
  14. 14.
    Checko, A. (2016). Cloud radio access network architecture. Towards 5G mobile networks. Technical University of Denmark.Google Scholar
  15. 15.
    Chekol, A. T. (2017). Performance analysis of cloud radio access network. Trondheim: NTNU.Google Scholar
  16. 16.
    Jiang, M., Condoluci, M., & Mahmoodi, T. (2016). Network slicing management and prioritization in 5G mobile systems. In Proceedings of European wireless 2016; 22th European wireless conference (pp. 1–6).Google Scholar
  17. 17.
    Richart, M., Baliosian, J., Serrat, J., Gorricho, J.-L., Agüero, R., & Agoulmine, N. (2017). Resource allocation for network slicing in WiFi access points. In 2017 13th International conference on network and service management (CNSM), 26–30 Nov (pp. 1–6).Google Scholar
  18. 18.
    Kamel, M. I., Le, L. B., & Girard, A. (2014). LTE wireless network virtualization: Dynamic slicing via flexible scheduling. In 2014 IEEE 80th Vehicular technology conference (VTC Fall) (pp. 1–5).Google Scholar
  19. 19.
    Wierman, A., Winands, E. M., & Boxma, O. J. (2007). Scheduling in polling systems. Performance Evaluation, 64, 1009–1028.CrossRefGoogle Scholar
  20. 20.
    Bertsekas, D. P., Gallager, R. G., & Humblet, P. (1987). Data networks (Vol. 2). Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  21. 21.
    Kleinrock, L., & Levy, H. (1988). The analysis of random polling systems. Operations Research, 36, 716–732.MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Kleinrock, L. (1976). Queueing systems, volume 2: Computer applications (Vol. 66). New York: Wiley.zbMATHGoogle Scholar
  23. 23.
    Fuhrmann, S. (1985). Symmetric queues served in cyclic order. Operations Research Letters, 4, 139–144.MathSciNetCrossRefzbMATHGoogle Scholar
  24. 24.
    Cosmetatos, G. P. (1976). Some approximate equilibrium results for the multi-server queue (M/G/r). Journal of the Operational Research Society, 27, 615–620.CrossRefzbMATHGoogle Scholar
  25. 25.
    Kimura, T. (1994). Approximations for multi-server queues: System interpolations. Queueing Systems, 17, 347–382.MathSciNetCrossRefzbMATHGoogle Scholar
  26. 26.
    de Moraes, L. F., & Silva, R. S. (2014). Analysis of multichannel wireless networks with priority-based polling MAC protocols. In Wireless days (WD), 2014 IFIP (pp. 1–6).Google Scholar

Copyright information

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

Authors and Affiliations

  • Salman Ali AlQahtani
    • 1
  • Abdulaziz Saud Altamrah
    • 1
  1. 1.Department of Computer EngineeringKing Saud University, College of Computer and Information SciencesRiyadhSaudi Arabia

Personalised recommendations