Computational complexity reduction of an adaptive congestion control in Active Queue Management

Active queue management (AQM) policies provide an early indication of incipient congestion to the source. In this paper, we propose a new AQM policy that predicts the instantaneous queue length at the next time instant using adaptive filtering technique. To use this algorithm in fast routers, we have reduced its computational complexity. The proposed method uses a simple linear function as adaptive rule. We show that this adaptive congestion control method is able to control the oscillations in the instantaneous queue length. We compare the performance of our method with the other well-known AQM methods such as RED and PI which are also simulated by MATLAB. We also compare the computational complexity of these algorithms with each other.