An Approach for Congestion Detection in Ad-hoc Networks
Keywords:
Congestion detection, Mobile Ad-hoc Networks (MANETs), Random Early Detection, Round-trip time, Traditional congestion control, Wireless networksAbstract
Congestion detection and control in ad-hoc networks is a significant challenge due to dynamic topology, limited bandwidth, and decentralized management. Traditional congestion control techniques, primarily designed for wired networks, often fail in mobile environments where frequent disconnections and mobility cause unpredictable behavior. This paper proposes a lightweight and adaptive approach for congestion detection in ad-hoc networks by analyzing packet delivery metrics such as queue length, round-trip time, and packet inter-arrival variance. The method utilizes threshold-based anomaly detection combined with cross-layer feedback mechanisms to identify early signs of congestion. Simulation results demonstrate that the proposed approach significantly reduces packet loss, average delay, and improves throughput when compared with conventional protocols like AODV-RED, DSR-ECN, and TCP Vegas. This research contributes toward developing robust and efficient routing strategies in highly dynamic ad-hoc networks, supporting performance-sensitive applications such as emergency response, military operations, and vehicular communication.
References
M. U. Ghazi, S. S. H. Naqvi, K. Yamin, and O. Humayun, “Congestion-Aware Routing Algorithm Based on Traffic Priority in Wireless Sensor Networks,” 2018 15th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT (HONET-ICT), pp. 112–116, Oct. 2018, doi: https://doi.org/10.1109/honet.2018.8551337.
A. H. Mohsin and K. A. Bakar, “Optimal control overhead based multi-metric routing for MANET,” Wireless Networks, vol. 24, no. 6, pp. 2319–2335, Feb. 2017, doi: https://doi.org/10.1007/s11276-017-1468-3.
L. S. Brakmo and L. L. Peterson, “TCP Vegas: end to end congestion avoidance on a global Internet,” IEEE Journal on Selected Areas in Communications, vol. 13, no. 8, pp. 1465–1480, 1995, doi: https://doi.org/10.1109/49.464716.
M. Gerla, M. Y. Sanadidi, Ren Wang, A. Zanella, C. Casetti, and S. Mascolo, “TCP Westwood: congestion window control using bandwidth estimation,” GLOBECOM’01. IEEE Global Telecommunications Conference (Cat. No.01CH37270), 2002, doi: https://doi.org/10.1109/glocom.2001.965869.
V. D. Park and M. S. Corson, “A highly adaptive distributed routing algorithm for mobile wireless networks,” International Conference on Computer Communications, Apr. 1997, doi: https://doi.org/10.1109/infcom.1997.631180.
D. Kliazovich and F. Granelli, “Cross-layer congestion control in ad hoc wireless networks,” Ad Hoc Networks, vol. 4, no. 6, pp. 687–708, Nov. 2006, doi: https://doi.org/10.1016/j.adhoc.2005.08.001.
T. D. Dyer and R. V. Boppana, “A comparison of TCP performance over three routing protocols for mobile ad hoc networks,” Mobile Ad Hoc Networking and Computing, Oct. 2001, doi: https://doi.org/10.1145/501422.501425.
G. Suresh, S. Kumar, V. Kavitha, and S. Lekashri, “Forecast Function Based Congestion Control in MANET Routing,” IOP Conference Series: Materials Science and Engineering, vol. 925, no. 1, p. 012074, Sep. 2020, doi: https://doi.org/10.1088/1757-899x/925/1/012074.
A. Paranjothi, M. S. Khan, and S. Zeadally, “A Survey on Congestion Detection and Control in Connected Vehicles,” Ad Hoc Networks, p. 102277, Jul. 2020, doi: https://doi.org/10.1016/j.adhoc.2020.102277.
W. Feng, K. G. Shin, D. D. Kandlur, and D. Saha, “The BLUE active queue management algorithms,” IEEE ACM Transactions on Networking, vol. 10, no. 4, pp. 513–528, Aug. 2002, doi: https://doi.org/10.1109/tnet.2002.801399.
