Cloud computing; Internet of Things; Scheduling; Quality of Service
In our research, we generate datasets utilizing two key statistical models: the Poisson Process Distribution and the Beta Distribution. These models are employed to simulate and analyze various aspects of Quality of Service (QoS) in Internet of Things (IoT) environments, with a particular emphasis on wireless communications. By leveraging these distributions, our study aims to optimize resource allocation, improve reliability, and ensure that QoS requirements are met in complex and dynamic wireless communication scenarios within IoT ecosystems.
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Currently, Internet applications running on mobile devices generate a massive amount of data that can be transmitted to a Cloud for processing. However, one fundamental limitation of a Cloud is the connectivity with end devices. Fog computing overcomes this limitation and supports the requirements of time-sensitive applications by distributing computation, communication, and storage services along the Cloud to Things (C2T) continuum, empowering potential new applications, such as smart cities, augmented reality (AR), and virtual reality (VR).
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