Modern telecommunication networks face new challenges with the ever-increasing number of connected devices (which range from household appliances and wearable gadgets to industrial machinery and vehicles). More transmitters lead to increased network congestion, which raises the likelihood of signal corruption, thereby leading individual policies to be more aggressive, which in turn further exacerbate congestion. This positive feedback loop can severely impact the quality of service. In this talk, we explore mean field models in discrete time and state that treat congestion as an endogenous effect of the network's overall policy. We present theoretical results on the existence and uniqueness of solutions and conduct numerical experiments demonstrating that, in certain situations, congestion can be reduced by up to a factor of three using our approach.
Idriss Mazari