Random Early Detection utilizing genetics algorithm

Application requirements for delay and low jitter has driven the development of Active Queue Management (AQM) is very fast. Random Early Detection (RED) as one of the AQM has grown so rapidly and become a reference for the development of other AQM variants. RED to be fast growing because of its simplicity and ease to modified its parameter. There have been many studies that discuss the development of RED, but very few have focused on finding w_q value, the weights for the optimal packet drop probability. In this study we tried to offer a different approach to the search w_q values using genetic algorithms. This is done to adapt the possible values w_q dynamically according to the character of traffic.