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

Samuel Oluwatosin Hassan (Olabisi Onabanjo University)
Adewole Usman Rufai (University of Lagos)
Vivian Ogochukwu Nwaocha (National Open University)
Samson Ojo Ogunlere (Babcock Uniersity)
Aderonke Adelola Adegbenjo (Babcock University)
Michael Olugbenga Agbaje (Babcock University)
Theophilus Aniemeka Enem (Air Force Institute of Technology)

International Journal of Electrical and Computer Engineering
Vol 13, No 1: February 2023

Network congestion is still a problem on the internet. The random early detection (RED) algorithm being the most notable and widely implemented congestion algorithm in routers faces the problems of queue instability and large delay arising from the presence of an ineffectual singular linear packet dropping function. This research article presents a refinement to RED, named quadratic exponential random early detection (QERED) algorithm, which exploits the advantages of two drop functions, namely quadratic and exponential in order to enhance the performance of RED algorithm. ns-3 simulation studies using various traffic load conditions to assess and benchmark the effectiveness of QERED with two improved variants of RED affirmed that QERED offers a better performance in terms of average queue size and delay metrics at various network scenarios. Fortunately, to replace/upgrade the implementation for RED algorithm with QERED’s in routers will require minimal effort due to the fact that nothing more besides the packet dropping probability profile got to be adjusted.