atio of the simulated values (with equation (4.1)). Moreover, Figure 6.13 presents the lub link utilization obtained with equation (6.8) and (6.9) and compared with simulations. Dimensioning of voice traffic with CAC reject ratio B = 1% offered traffic A [Erlang] 19.24 47.75 86.81 128.27 166.7 256.82 335.18 461.07 Dimensioning of voice traffic with CAC reject ratio B = 5% offered traffic A [Erlang] 44.49 87.32 130.34 169.61 250.45 332.84 457.2 Table 6.3: For a fixed CAC reject ratio (1% and 5%), the required number of channels n given the offered traffic A in Erlang 6.2 Dimensioning for Circuit-Switched Traffic 1% CAC reject rato Voice 1% CAC reject ratio Voice Erlang-B Simulations offered voice traffic [kbps] offered voice traffic [kbps] Figure 6.11: Validation of Erlang-B formula: dimensioning for 1% CAC reject ratio 5% CAC reject rato Voice 5% CAC reject ratio Voice Erlang-B Simulations offered voice traffic [kbps] offered voice traffic [kbps] Figure 6.12: Validation of Erlang-B formula: dimensioning for 5% CAC reject ratio 1% CAC reject ratio Voice 5% CAC reject ratio Voice Erlang-B Erlang-B Simulations Simulations offered voice traffic [kbps] offered voice traffic [kbps] Figure 6.13: Validation of Erlang-B formula for voice scenario: CAC reject ratio and link utilization over offered voice traffic Through comparing the simulation results against the analytical results derived from the Erlang-B model in the above figures, it is observed that the Erlang-B model results in a 6 Dimensioning for Single ATM-Based lub precise estimation for the dimensioning for a fixed CAC reject ratio. The caused relative error is low, in a range of 0 to 5%. So it can be concluded that the Erlang-B formula is an accurate analytical model for dimensioning streaming traffic with a fixed CAC reject ratio in a single traffic stream scenario. The Erlang-B model is simple to calculate, and furthermore due to its insensitivity to the service time distribution, it can be widely applied to other streaming traffic such as video streaming. I