Diffusion based statistical call admission control in ATM
We propose a call admission control (CAC) procedure for asynchronous transfer mode (ATM) networks using statistical bandwidth as the decision criterion, based on closed-form expressions that use diffusion models. This approach is computationally very efficient and easily implementable. It is related to Gaussian approximations previously proposed for CAC, though our expressions are derived from a more derailed representation of traffic and the buffer length process, The statistical bandwidth expressions we use take into consideration the users' cell loss requirements, their aggregate traffic characteristics, the available buffer size at the statistical multiplexers, and capture the interaction between individual traffic streams at the ATM multiplexer. Extensive numerical and simulation results are presented to evaluate the efficiency and adequacy of this CAC procedure. Comparison with existing methods such as the Equivalent Bandwidths and Gaussian Approximations indicate that our approach remains conservative with respect to cell loss compared to previously proposed CAC schemes, yet that it is more economical in bandwidth allocation leading to larger admission regions both for homogeneous and heterogeneous traffic.
call admission control in atm statistical bandwidth quality of service diffusion queueing model