Improving the understanding of the dynamic properties of advanced communication networks by using agent-based modeling approach
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Date
2018-06
Authors
Nur Syazana Mat Yusof
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Abstract
Modern communication networks are getting more advanced and complex.
Therefore, complex systems become a new field for researchers to explore how aspects
of a system give rise to the collective behaviors of the system and how the system
interacts with its environment. The behavior of a complex system is how network
constituent act together to form the behavior of the whole, not only the behavior of the
constituent aspects. Such a complexity can be seen in the many types of advanced
communication networks such as wireless ad-hoc network, mobile sensor network, and
cognitive radio networks. In these networks, complexity and unpredictable arise from
the mobility, limited bandwidth, latency, interference from neighboring networks, and
typological changes. In addition, mobile stations in ad-hoc networks are expected to be
autonomous in making their own decision and to cooperate with other mobile stations in
organizing the network. This rising complexity of the communication networks has a
profound implication for modeling and simulation. As the networks are becoming more
complex, testing and evaluation of the design and implementation are becoming more
difficult. There are many existing models used to depict complex networks. This project
use new modeling and simulation approach, which is the agent-based modeling
approach. Thus, this project will go through a software model named as Netlogo to aid
in understanding and conceptualizing about this project. The results show that agent-based modeling is a better model compared to traditional models such as Swarm and
MASON, especially when modeling complex communication networks.