TY - JOUR AU - Rohit P. Tahiliani AU - Sagar Sachdeva AU - Sachin Hadke AU - Shane Sheehan AU - Eamonn O' Nuallain PY - 2018/03/22 Y2 - 2024/03/29 TI - Evaluation of Random Early Detection and Adaptive Random Early Detection in Benchmark Scenarios JF - Journal of Information Sciences and Computing Technologies JA - JISCT VL - 7 IS - 1 SE - Articles DO - UR - http://scitecresearch.com/journals/index.php/jisct/article/view/1408 AB - In this paper, we evaluate Random Early Detection (RED) and Adaptive RED (ARED) in Benchmark Scenarios as detailed in RFC 7928. RED is one of the early proposed AQM mechanisms, which attains high throughput and keeps average delay low. Moreover, ARED is an extension to RED which eliminates the parameter sensitivity to improve the performance of RED. The results indicate that RED outperforms ARED in scenarios with abrupt changes in traffic load. ARED is known to reduce the packet drops and therefore, in rest of the scenarios it can be observed that ARED outperforms RED. ER -