Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach

Background: Computer Networks have a tendency to grow at an unprecedented
scale. Modern networks involve not only computers but also a wide variety
of other interconnected devices ranging from mobile phones to other
household items fitted with sensors. This vision of the "Internet of
Things" (IoT) implies an inherent difficulty in modeling problems.
Purpose: It is practically impossible to implement and test all scenarios
for large-scale and complex adaptive communication networks as part of
Complex Adaptive Communication Networks and Environments (CACOONS). The
goal of this study is to explore the use of Agent-based Modeling as part
of the Cognitive Agent-based Computing (CABC) framework to model a Complex
communication network problem. Method: We use Exploratory Agent-based
Modeling (EABM), as part of the CABC framework, to develop an autonomous
multi-agent architecture for managing carbon footprint in a corporate
network. To evaluate the application of complexity in practical scenarios,
we have also introduced a company-defined computer usage policy. Results:
The conducted experiments demonstrated two important results: Primarily
CABC-based modeling approach such as using Agent-based Modeling can be an
effective approach to modeling complex problems in the domain of IoT.
Secondly, the specific problem of managing the Carbon footprint can be
solved using a multiagent system approach.