This paper presents the study of the hyper-Erlang distribution model and its applications in wireless networks and mobile computing systems. We demonstrate that the hyper-Erlang models provides a very general model for users' mobility and may provide viable approximations to fat-tailed distributions which lead to the self-similar traffic. We apply the hyper-Erlang distribution to model the cell residence time (for users' mobility) and demonstrate the effect on channel holding time. This research opens a new avenue for traffic modeling and performance evaluation for wireless networks and mobile computing systems.
['Yuguang Fang']
Hyper-Erlang distributions and traffic modeling in wireless and mobile networks