Enhanced Random Early Detection using Responsive Congestion Indicators

Random Early Detection (RED) is an Active Queue Management (AQM) method proposed in the early 1990s to reduce the effects of network congestion on the router buffer. Although various AQM methods have extended RED to enhance network performance, RED is still the most commonly utilized method; this is because RED provides stable performance under various network statuses. Indeed, RED maintains a manageable buffer queue length and avoids congestion resulting from an increase in traffic load; this is accomplished using an indicator that reflects the status of the buffer and a stochastic technique for packet dropping. Although RED predicts congestion, reduces packet loss and avoids unnecessary packet dropping, it reacts slowly to an increase in buffer queue length, making it inadequate to detect and react to sudden heavy congestion. Due to the aforementioned limitation, RED is found to be significantly influenced by the way in which the congestion indicator is calculated and used. In this paper, RED is modified to enhance its performance with various network statuses. RED technique is modified to overcome several disadvantages in the original method and enhance network performance. The results indicate that the proposed Enhanced Random Early Detection (EnRED) and Time-window Augmented RED (Windowed-RED) methods—compared to the original RED, ERED and BLUE methods—enhances network performance in terms of loss, dropping and packet delay.

@article{Abu-Shareha2019,
  title     = {Enhanced Random Early Detection using Responsive Congestion Indicators},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {3},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Ahmad Adel Abu-Shareha},
  doi       = {10.14569/IJACSA.2019.0100347},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100347}
}