An Improvement over Random Early Detection Algorithm: A Self-Tuning Approach

Jamali, S.; Alipasandi, N.; Alipasandi, B.

doi:10.22061/jecei.2014.242

Document Type : Original Research Paper

Authors

¹ Computer Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran

² Sama technical and vocational training college, Islamic Azad University, Ardabil Branch, Ardabil, Iran

³ Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran

https://doi.org/10.22061/jecei.2014.242

Abstract

Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed values is not an efficient solution. We propose a new method to dynamically tuning RED's parameters. For this purpose, we compute the rate of which the queue is occupied and consider it as a congestion metric that will be forecasted when the queue is overloaded. This meter is used to dynamically setting RED parameters. The simulation results show the effectiveness of the proposed method. According to the results, we achieve a significantly higher utilization and less packet loss comparing to original RED algorithm in dynamic conditions of the network.

Keywords

20.1001.1.23223952.2014.2.2.1.0

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Journal of Electrical and Computer Engineering Innovations (JECEI)

An Improvement over Random Early Detection Algorithm: A Self-Tuning Approach

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References

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Volume 2, Issue 2 - Serial Number 4
July 2014
Pages 57-61

An Improvement over Random Early Detection Algorithm: A Self-Tuning Approach

References

References

Send comment about this article

Volume 2, Issue 2 - Serial Number 4July 2014Pages 57-61

Volume 2, Issue 2 - Serial Number 4
July 2014
Pages 57-61