How mobility impacts the flow-level performance of wireless data networks
The potential for exploiting rate variations to improve the performance of wireless data networks by opportunistic scheduling has been extensively studied at the packet level. In the present paper, we examine how slower, mobility-induced rate variations impact the performance at the flow level, accounting for the dynamic number of users sharing the transmission resource. We identify two limit regimes, termed fluid regime and quasi-stationary regime, where the rate variations occur on an infinitely fast and an infinitely slow time scale, respectively. Using stochastic comparison techniques, we show that these limit regimes provide simple, insensitive performance bounds that only depend on easily calculated load factors. Additionally, we prove that for a broad class of Markov-type fading processes, the performance varies monotonically with the time scale of the rate variations. The results are illustrated through numerical experiments, showing that the fluid and quasi-stationary bounds are remarkably sharp in certain typical cases.