Energy Efficient IoT Networks Using AI-Driven Approaches
DOI:
https://doi.org/10.22105/scfa.v2i1.38Keywords:
Internet of things, Energy management, Multi-agent system, Genetic algorithm, Energy optimization, MATLAB Simulink simulation, Energy efficiencyAbstract
The idea of a connected world through the Internet of Things (IoT) has already materialized in this decade. The advancement of efficient hardware and high-capacity networks has made it possible for billions of devices to link, gather, and relay useful information. One of the main advantages of IoT devices is their capability to automate processes; however, the vast amount of energy needed for billions of connected devices to interact can pose a significant challenge to the full realization of IoT systems if not carefully managed. This paper introduces a system for managing energy in IoT devices, considering both hardware and software dimensions. Energy transparency has been achieved by modeling the energy utilized during sensing, processing, and communication activities. A multi-agent system has been developed to represent the IoT devices and their energy usage. To optimize the parameters of the multi-agent system, a genetic algorithm has been employed. Lastly, simulation tools like MATLAB Simulink and OpenModelica are utilized to evaluate the system. The results of the optimization indicate considerable energy savings when implementing the decentralized intelligence of the multi-agent system.
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