SARED: A Self-Adaptive Active Queue Management Scheme for Improving Quality of Service in Network Systems

Abstract

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.

Quadratic exponential random early detection: a new enhanced random early detection-oriented congestion control algorithm for routers

“…In today's world, the internet has been described as an advanced technology which drives speedy development of the society as it supports contemporary communication, information sharing and services [1], [2]. Congestion control still continues as an active research area in the current internet due to huge magnitude of traffic triggered by users accessing internet services [3]- [7]. Network congestion refers to a condition in which the amount of generated traffic grows and exceeds network's resources processing capacity [3], [8].…”

“…Congestion control still continues as an active research area in the current internet due to huge magnitude of traffic triggered by users accessing internet services [3]- [7]. Network congestion refers to a condition in which the amount of generated traffic grows and exceeds network's resources processing capacity [3], [8]. It is one of the crucial problems that affect quality of network service [9], [10].…”

“…RED_E was reported to obtain an improved performance in terms of delay especially at heavy congestion scenario. Adamu [3] developed the self-adaptive RED (SARED) algorithm which relies on the computation of average queue size and current network traffic condition as indicators for congestion. Therefore, at low and moderate network traffic scenarios, a nonlinear packet dropping function is utilized in order to improve the throughput performance.…”

Improved random early detection congestion control algorithm for internet routers

“…Network congestion is a situation in which the size/amount of generated data traffic exceeds the capacity of network's resource. In the Internet, a key resource like routers play a crucial role of handling large traffic loads is affected by congestion [3]. Congestion has an adverse effect of degrading network performance [5]- [7].…”

RED-LE: A Revised Algorithm for Active Queue Management

“…Network congestion may be described as a condition in which the amount of incoming data packets (generated traffic) is greater than the amount that the network's available resources are capable of accommodating [1]- [5]. The problem of network congestion affects the quality of service (QoS), as it leads to high packet delays, loss rates, and low throughput [2], [4], [5]- [9]. A router plays an important role in the process of controlling network congestion, as it allows to achieve improved network performance rates [9].…”