1 research outputs found
Agent-Based Modelling Approach for Distributed Decision Support in an IoT Network
An increasing number of emerging applications, e.g., internet of things,
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 model the
communication aspects of a road traffic management system, as an example of an
Internet of Things (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 show the importance of coordination between
multiple decision makers in order to improve the accuracy of information and
spectrum utilization of the system