Simulation of Collision Resolution Algorithm based on self-similar traffic model

The traditional traffic models are mostly based on Poisson model or Bernoulli process. However, in recent decade, it has been found in traffic measurements the coexistence of both long-range and short-range dependences in network traffic. Collision resolution algorithm (CRA) is an efficient strategy to improve the performance of multiple access protocols, and achieves the highest capacity among all known multiple access protocols under the Poisson traffic model. In this paper, extensive simulation experiments are conducted to obtain the performances of CRA under the self-similar traffic model. Two traffic models are examined: (1) the fractional autoregressive integrated moving average (FARIMA) process with non-Gaussian white driving sequence; (2) real traffic traces captured at a well-attended ACM conference. Our study demonstrates that the existing well-known algorithms must be improved to adapt the self-similar traffic model.