Impact of self-similarity on the go-back-N ARQ protocols

Packet traffic exhibits fractal or self-similar properties which are fundamentally different from features found in circuit switched voice traffic and captured by commonly used theoretical traffic models. These fractal properties are associated with the burstiness of packet traffic. In this paper we examine the impact of self-similarity on the link-layer error control mechanism, in particular, the most commonly used go-back-N automatic-repeat-request (ARQ) protocols. Our analysis indicates that in terms of the maximum throughput efficiency, the go-back-a protocol does achieve higher efficiency under the self-similar errors compared to the random error model. We also see that, assuming the underlying channel error process is self-similar, the Gilbert´s 2-state error model does not predict the maximum throughput efficiency well; even with the parameter matching technique, we showed that the Gilbert´s model only matches the maximum throughput efficiency well when the ratio of propagation delay to the frame transmission time is small. Self-similar traffic has higher delay compared to Poisson traffic for a given error model. For a given traffic stream, we see that the delay performance predicted by the conventional error models does not match the performance based on the self-similar error model. This suggests that conventional error models cannot capture the behavior of the go-back-N ARQ system performance. In general, with self-similar traffic and/or self-similar errors, network engineering needs to be more conservative than that based on conventional traffic and/or error models