Abstract
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 model provides a very general model for users' mobility and may provide a viable approximation to fat-tailed distribution which leads to the self-similar traffic. The significant difference from the traditional approach in the self-similarity study is that we want to provide an approximation model which preserves the Markovian property of the resulting queueing systems. We also illustrate that the hyper-Erlang distribution is a natural model for the characterization of the systems with mixed types of traffics. As an application, 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 may open a new avenue for traffic modeling and performance evaluation for future wireless networks and mobile computing systems, over which multiple types of services (voice, data or multimedia) will be supported.
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Fang, Y. Hyper-Erlang Distribution Model and its Application in Wireless Mobile Networks. Wireless Networks 7, 211–219 (2001). https://doi.org/10.1023/A:1016617904269
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DOI: https://doi.org/10.1023/A:1016617904269