Skip to main content

Advertisement

SpringerLink
Log in

A genetic fuzzy contention window optimization approach for IEEE 802.11 WLANs

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The role of IEEE 802.11 wireless local area networks (WLANs) become vital due to its low cost deployment and the aspiration to improve its performance has become the need of the day. Among existing challenges the most prominent are success ratio, packet loss ratio, collision rate, fairness index, and energy consumption, advances in wireless technologies stress to surmount these challenges. To attain these, performance enhancement, genetic fuzzy-contention window optimization (GF-CWO) approach, is proposed which combined the fuzzy logic controller (FLC) and genetic algorithm (GA), through this way GA optimally tuned the FLC. For this purpose three alogrithms are proposed, namely Algorithm-1: GF-CWO for WLANs, Algorithm-2: GA for GF-CWO, and Algorithm-3: FLC for GF-CWO. Proposed GF-CWO approach is tested for binary exponential back-off (BEB), selected being a de facto standard algorithm, and for Channel Status based Sliding Contention Window (CS-SCW) algorithm, selected being a fuzzy logic based algorithm, implemented in MATLAB. Recorded the resultant values for 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 nodes in different files for BEB, CS-SCW, and GF-CWO, respectively. Later on these files were used to evaluate success ratio, packet loss ratio, collision rate, fairness index and energy consumption and also generated the results graphically. The results generated through simulated test confirmed that the GF-CWO has effectively enhanced the performance.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Committee ICSLMS et al. (2016) IEEE standard for information technology—Telecommunications and information exchange between systems local and metropolitan area networks—Specific requirements—Part 11: Wireless lan medium access control (MAC) and physical layer (PHY) specifications. IEEE Std 80211-2016 (Revision of IEEE Std 80211-2012).

  2. Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535–547.

    Article  Google Scholar 

  3. Hoang, T. M., Bui, V. K., & Nguyen, T. T. (2017). The performance evaluation of an IEEE 802.11 network containing misbehavior nodes under different backoff algorithms. Security and Communication Networks, 2017, 1–8.

  4. Lei, J., Wang, Y., & Yun, H. (2020). Decoupling-based channel access mechanism for improving throughput and fairness in dense multi-rate WLANS. Future Internet, 12(1), 3.

    Article  Google Scholar 

  5. Lei, J., Tao, J., Huang, J., & Xia, Y. (2019). A differentiated reservation mac protocol for achieving fairness and efficiency in multi-rate IEEE 802.11 WLANS. IEEE Access, 7, 12133–12145.

    Article  Google Scholar 

  6. Zhong, Z., Kulkarni, P., Cao, F., Fan, Z., & Armour, S .(2015) . Issues and challenges in dense wifi networks. In 2015 International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 947–951). IEEE.

  7. Zhao, Q., Xu, F., Yang, J., & Zhang, Y. (2017). CSMA/CQ: A novel SDN-based design to enable concurrent execution of channel contention and data transmission in IEEE 802.11 networks. IEEE Access, 5, 2534–2549.

    Article  Google Scholar 

  8. Chun, S., Xianhua, D., Pingyuan, L., & Han, Z. (2012). Adaptive access mechanism with optimal contention window based on node number estimation using multiple thresholds. IEEE Transactions on Wireless Communications, 11(6), 2046–2055.

    Article  Google Scholar 

  9. Al-Hubaishi, M., Alahdal, T., Alsaqour, R., Berqia, A., Abdelhaq, M., & Alsaqour, O. (2014). Enhanced binary exponential backoff algorithm for fair channel access in the IEEE 802.11 medium access control protocol. International Journal of Communication Systems, 27(12), 4166–4184.

    Article  Google Scholar 

  10. Patel, P., & Lobiyal, D. K. (2015). A simple but effective contention aware and adaptive back-off mechanism for improving the performance of IEEE 802.11 DCF. Wireless Personal Communications, 83(3), 1801–1841.

    Article  Google Scholar 

  11. Syed, I., & Roh, B. (2016). Adaptive backoff algorithm for contention window for dense IEEE 802.11 WLANS. Mobile Information Systems, 2016, 1–11.

  12. Zhou, X., Zheng, C., & Liao, M. (2016). Full-feedback contention window adaption for IEEE 802.11 WLANS. Journal of Systems Engineering and Electronics, 27(1), 90–98.

    Google Scholar 

  13. Shurman, M., & Al-Shua’b, B. (2016). N-beb: New binary exponential back-off algorithm for IEEE 802.11. Adhoc & Sensor Wireless Networks, 32, 301–317.

  14. Zhang, C., Chen, P., Ren, J., Wang, X., & Vasilakos, A. V. (2017). A backoff algorithm based on self-adaptive contention window update factor for IEEE 802.11 DCF. Wireless Networks, 23(3), 749–758.

    Article  Google Scholar 

  15. Hanzawa, T., & Kimura, S. (2017). A minimum contention window control method for lowest priority based on collision history of wireless LAN. International Journal of Networking and Computing, 7(2), 295–317.

    Article  Google Scholar 

  16. Karaca, M., Bastani, S., & Landfeldt, B. (2017). Modifying backoff freezing mechanism to optimize dense IEEE 802.11 networks. IEEE Transactions on Vehicular Technology, 66(10), 9470–9482.

    Article  Google Scholar 

  17. Choi, J., Byeon, S., Choi, S., & Lee, K. B. (2017). Activity probability-based performance analysis and contention control for IEEE 802.11 WLANS. IEEE Transactions on Mobile Computing, 16(7), 1802–1814.

    Article  Google Scholar 

  18. Nithya, B., Mala, C., & Sivasankar, E. (2017). Channel status based sliding contention window (cs-scw) algorithm: A fuzzy control approach for medium access in wireless networks. Soft Computing, 21(8), 1991–2004.

    Article  Google Scholar 

  19. Lee, M. W., & Hwang, G. (2018). Adaptive contention window control scheme in wireless ad hoc networks. IEEE Communications Letters, 22(5), 1062–1065.

    Article  Google Scholar 

  20. Cai, X., Li, B., Yang, M., Yan, Z., Yang, B., Jin, Y., & Li, X. (2018). Fractional backoff algorithm for the next generation WLAN. In International wireless internet conference (pp. 24–31). Springer.

  21. Cheng, Y., Zhou, H., & Yang, D. (2019). Ca-CWA: Channel-aware contention window adaption in IEEE 802.11 ah for soft real-time industrial applications. Sensors, 19(13), 3002.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad Campus, Islamabad, Pakistan

    Imran Ali Qureshi

  2. Department of Computer Science, Comsats University Islamabad, Islamabad, Pakistan

    Sohail Asghar

Authors
  1. Imran Ali Qureshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sohail Asghar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Imran Ali Qureshi.

Ethics declarations

Conflicts of interest

Authors declare that they have no conflicts of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

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

Qureshi, I.A., Asghar, S. A genetic fuzzy contention window optimization approach for IEEE 802.11 WLANs. Wireless Netw 27, 2323–2336 (2021). https://doi.org/10.1007/s11276-021-02572-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-021-02572-8

Keywords

Search

Navigation