The extended alternating fractal renewal process for modeling traffic in high-speed communication networks

Extensive studies indicate that traffic in high-speed communication network s exhibits long-range dependence (LRD) and impulsiveness, which pose new ch allenges in network engineering. While many models have recently appeared f or capturing the traffic LRD, fewer models exist that account for impulsive ness as well as LRD. One of the few existing constructive models for networ k traffic is the celebrated on/off model or the alternating fractal renewal process (AFRP). However, although the AFRP results in aggregated traffic w ith LRD, it fails to capture impulsiveness, yielding traffic with Gaussian marginal distribution. A new constructive model, namely the extended AFRP ( EAFRP), is proposed here, which overcomes the limitations of the AFRP model . We show that for both single-user and aggregated traffic, it results in i mpulsiveness and long-range dependence, the LRD being defined here in a gen eralized sense. We provide queueing analysis of the proposed model, which c learly demonstrates the implications of the impulsiveness in traffic engine ering, and validate all theoretical findings based on real traffic data.