JACIII Vol.24 No.5 pp. 615-620
doi: 10.20965/jaciii.2020.p0615


Improving Fairness in IEEE 802.11 EDCA Ad Hoc Networks Based on Fuzzy Logic

Luong Duy Hieu*,†, Bui The Tung**, Pham Thanh Giang**, Thai Quang Vinh**, and Le Nam**

*Department of Computer Science, FPT University
113 Tran Duy Hung Street, Cau Giay District, Hanoi, Vietnam

**Institute of Information Technology, Vietnam Academy of Science and Technology
18 Hoang Quoc Viet Street, Cau Giay District, Hanoi, Vietnam

Corresponding author

March 4, 2020
May 24, 2020
September 20, 2020
IEEE 802.11, fuzzy logic, MAC control, QoS, EDCA
Improving Fairness in IEEE 802.11 EDCA Ad Hoc Networks Based on Fuzzy Logic

Fuzzy logic controller

Wireless ad hoc network is a self-configurable and dynamically distributed network in which stations can move freely. In the ad hoc network, some flows have difficulty in accessing the channel due to contention at both the medium-access control (MAC) and link layers. The IEEE 802.11 protocol is currently the de facto standard for wireless networks. It uses enhanced distributed channel access (EDCA) method to access the transmission environment of each type of data flow. The size of the contention window (CW) in EDCA is related to the probability of accessing the channel of each flow. In our approach, useful information is obtained from the physical, MAC, and link layers. A fuzzy logic system is then used to adjust the size of CW to rely on such value, thereby improving the fairness index of data flows (voice, video, best effort) in IEEE 802.11 EDCA. The simulation results show that the proposed method can improve the throughput and fairness index of data flows.

Cite this article as:
L. Hieu, B. Tung, P. Giang, T. Vinh, and L. Nam, “Improving Fairness in IEEE 802.11 EDCA Ad Hoc Networks Based on Fuzzy Logic,” J. Adv. Comput. Intell. Intell. Inform., Vol.24, No.5, pp. 615-620, 2020.
Data files:
  1. [1] Q. Ni, L. Romdhani, and T. Turletti, “A Survey of QoS Enhancements for IEEE 802.11 Wireless LAN,” J. of Wireless Communications and Mobile Computing, Vol.4, No.5, pp. 547-566, 2004.
  2. [2] P. Durbha and M. Sherman, “Quality of Service (QoS) in IEEE 802.11 Wireless Local Area Networks: Evaluation of Distributed Coordination Function (DCF) and Point Coordination Function (PCF),” 2002 IEEE Int. Conf. on Communications (ICC), 2002.
  3. [3] IEEE, “802.11e-2005 – IEEE Standard for Information technology–Local and metropolitan area networks–Specific requirements–Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications – Amendment 8: Medium Access Control (MAC) Quality of Service Enhancements,” 2005.
  4. [4] T. J. Ross, “Fuzzy Logic With Engineering Applications,” Wiley India Private Ltd., 2011.
  5. [5] C.-L. Chen, “IEEE 802.11e EDCA QoS Provisioning with Dynamic Fuzzy Control and Cross-Layer Interface,” Proc. of 16th Int. Conf. on Computer Communications and Networks, pp. 766-771, 2007.
  6. [6] H. Touil and Y. Fakhri, “A Fuzzy-based QoS Maximization Protocol for WiFi Multimedia (IEEE 802.11e) Adhoc Networks,” Int. J. of Communication Networks and Information Security (IJCNIS), Vol.6, No.3, pp. 217-225, 2014.
  7. [7] A. E. Masri, N. Malouch, and H. Khalifé, “A Fuzzy-based Routing Strategy for Multihop Cognitive Radio Networks,” Int. J. of Communication Networks and Information Security (IJCNIS), Vol.3, No.1, pp. 74-82, 2011.
  8. [8] C. Kocak and H. B. Karakurt, “Fuzzy logic-based performance improvement on MAC layer in wireless local area networks,” Neural Computing and Applications, Vol.31, No.10, pp. 6113-6128, 2019.
  9. [9] M. Anuradha and G. Anandha Mala, “Cross-layer based congestion detection and routing protocol using fuzzy logic for MANET,” Wireless Networks, Vol.23, No.5, pp. 1373-1385, 2017.
  10. [10] P. T. Giang and K. Nakagawa, “Cross-Layer Scheme to Control Contention Window for Per-Flow in Asymmetric Multi-Hop Networks,” IEICE Trans. on Communications, Vol.E93.B, No.9, pp. 2326-2335, 2010.
  11. [11] “The Network Simulator – ns-2,” [accessed August 27, 2020]
  12. [12] R. Jain, D.-M. Chiu, and W. R. Hawe, “A quantitative measure of fairness and discrimination for resource allocation in shared computer systems,” DEC Research Report, Technical Report TR-301, 1984.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Dec. 01, 2020