On the Capacity Bounds for Bumblebee-Inspired Connected Vehicle Networks via Queuing Theory

摘要

The bumblebee has recently been proposed as a model to optimize channel allocation in connected vehicle networks where the quality of each channel varies unpredictably over time and space. A fundamental mathematical challenge that must be overcome before implementing the bumblebee model is determining the theoretical upper bound of spectrum optimization that can be achieved under such stochastic channel conditions. In this paper, we leverage the concept of queuing theory in order to conduct the performance bound analysis of bumblebee-inspired distributed optimization operation in vehicle-to-vehicle (V2V) environments. We initially established the maximum switching costs associated with urban and highway environment, and then used GEMV²and SUMO to compute the performance bounds for several metrics in a time-variant urban environment, including P_m(the probability of all channels being busy) and mean response time. We discuss the implications of these results for future development of bumblebee-inspired vehicular communication systems.