SARED: A Self-Adaptive Active Queue Management Scheme for Improving Quality of Service in Network Systems
Considering the phenomenal growth of network systems, congestion remains a threat to the quality of service provided in such systems, hence, research on congestion control is still relevant. Internet research community regards Active Queue Management (AQM) as an effective approach to address congestion in network systems. Most of the existing AQM schemes possess static drop patterns and lack self-adaptation mechanism, as such don’t work well for networks where traffic load fluctuates. This paper proposes Self-Adaptive Random Early Detection (SARED) scheme which smartly adapts its drop pattern based on current network’s traffic load in order to maintain better and stable performance. In light to moderate load conditions, SARED operates in nonlinear modes in order to maximize utilization and throughput, while in high load condition, it switches to linear mode in order to avoid forced drops and congestion. Experiments conducted have revealed that regardless of traffic load’s condition, SARED provides optimal performance.
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