Active Queue Management (AQM) methods are used to manage the buffer of the network routers and avoid the problems caused by network congestion, especially packet loss. Among various AQM methods that have been proposed in the literature, Random Early Detection (RED)method has proved to stabilize the network performance under various traffic loads. However, as the primary concern of RED is to avoid loss when the router buffer overflowed, RED harms the delay at the router and increases the latency. Given that reducing delay is critical to some applications, such as online conferencing and broadcasting, RED needs to be adjusted to ease the delay problem. In this paper, RED is improved by monitoring the delay at the router buffer and implementing packet dropping to handle the issue of network delay and enhance the network performance. Accordingly, the modified method calculates and used a delay parameter with the RED to reduce the delay while maintaining the desirable RED's characteristics. The experimental results showed that the proposed Delay-Controller Random Early Detection (DcRED) improved network performance under various traffic loads. Compared to RED, DcRED results in less delay, while maintaining the loss and dropping rates.
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.
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