Thesis supervisor: András Márkus
Location of studies (in Hungarian): SZTE Abbreviation of location of studies: SZTE
Description of the research topic:
The growth of the Internet of Things (IoT) has established a new era of data-driven applications, generating a massive volume of data from billions of interconnected devices. To process and analyze this data efficiently, IoT systems have adopted distributed architectures leveraging cloud, fog, and edge computing paradigms. DISSECT-CF-Fog is an open-source simulation environment that provides a comprehensive framework for modeling and evaluating systems and applications of the Cloud-to-Thing Continuum. The rapid growth and complexity of IoT-Fog-Cloud systems pose challenges in optimizing resource utilization, reducing latency, and minimizing energy consumption. The DISSECT-CF-Fog provides a robust simulation platform, thus, this PhD research aims the integration of AI-based optimization algorithms into the simulator to address these novel challenges effectively.
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