An Improvement over Random Early Detection Algorithm: ASelf-Tuning Approach

Publish Year: 1393
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_JECEI-2-2_001

تاریخ نمایه سازی: 15 آذر 1394

Abstract:

Random Early Detection (RED) is one of the most commonly used ActiveQueue Management (AQM) algorithms that is recommended by IETF fordeployment in the network. Although RED provides low average queuingdelay and high throughput at the same time, but effectiveness of RED ishighly sensitive to the RED parameters setting. As network conditionvaries largely, setting RED's parameters with fixed values is not anefficient solution. We propose a new method to dynamically tuning RED'sparameters. For this purpose, we compute the rate of which the queue isoccupied and consider it as a congestion metric that will be forecastedwhen the queue is overloaded. This meter is used to dynamically settingRED parameters. The simulation results show the effectiveness of theproposed method. According to the results, we achieve a significantlyhigher utilization and less packet loss comparing to original REDalgorithm in dynamic conditions of the network.

Authors

Shahram Jamali

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

Neda Alipasandi

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

Bita Alipasandi

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