A dynamic random exponential marking algorithm based queue factor and load factor

To solve the problem that random exponential marking (REM) suffered from some drawbacks such as big queue oscillations, sluggish response to dynamic network traffic and poor adaptability to various network conditions, the control property of REM was analyzed, and a dynamic REM (DREM) scheme was proposed. Control theory based analysis indicated that REM had the same property with proportional integral control. Additionally, two new variables, the queue factor and load factor, were introduced to divide the regulating procedure of queue length into four cases, which could identify the network status effectively. Moreover, the key parameter of REM was adjusted dynamically by using the queue factor and load factor to assist the 'additive increase multiplicative decrease (AIMD)' strategy-based TCP congestion control mechanism, and enhance the control performance of REM. Simulation and comparison with original REM in NS2 platform demonstrated that DREM could enhance the responsiveness of queue length, reduce the packet loss ratio, and improve the adaptability and robustness for active queue management.