<div>An increasing number of emerging applications, e.g.,</div>


<div>Internet of Things (IoT), vehicular communications, augmented reality,
and the growing complexity due to the interoperability requirements of
these systems, lead to the need to change the tools used for the
modeling and analysis of those networks. Agent-Based Modeling (ABM) as a
bottom-up modeling approach considers a network of autonomous agents
interacting with each other, and therefore represents an ideal framework
to comprehend the interactions of heterogeneous nodes in a complex
environment. Here, we investigate the suitability of ABM to</div>


<div>model the communication aspects of a road traffic management system as
an example of an IoT network. We model, analyze and compare various
Medium Access Control (MAC) layer protocols for two different scenarios,
namely uncoordinated and coordinated. Besides, we model the scheduling
mechanisms for the coordinated scenario as a high level MAC protocol by
using three different approaches: Centralized Decision Maker, DESYNC and
decentralized learning MAC (L-MAC). The results clearly</div>


<div>show the importance of coordination between multiple decision makers in
order to improve the information reporting error and spectrum
utilization of the system.</div>