The rapid proliferation of IoT devices and the increasing demand for real-time applications have driven a shift from traditional Cloud computing to Edge computing, giving rise to the Cloud-to-Things Continuum (C2TC). Many real-time IoT applications involve Mobile Nodes (MNs), such as autonomous vehicles and mobile robots, and require low-latency and high reliability. The optimal organization of the C2TC is crucial to meeting diverse application requirements while ensuring efficient resource allocation. In this paper, we analyze different C2TC configurations, leveraging multiple edge computing layers to optimize real-time application performance. We employ J-NECORA, an analytical tool designed to determine the optimal allocation of applications within C2TC at the design stage. Our findings demonstrate that the best allocation strategy depends on system-specific parameters, and J-NECORA effectively facilitates the comparison of different configurations, enabling informed decision-making.

Designing an Efficient Cloud-to-Things Continuum for Real-Time Mobile Applications

Pettorali, Marco;Righetti, Francesca;Anastasi, Giuseppe
2025-01-01

Abstract

The rapid proliferation of IoT devices and the increasing demand for real-time applications have driven a shift from traditional Cloud computing to Edge computing, giving rise to the Cloud-to-Things Continuum (C2TC). Many real-time IoT applications involve Mobile Nodes (MNs), such as autonomous vehicles and mobile robots, and require low-latency and high reliability. The optimal organization of the C2TC is crucial to meeting diverse application requirements while ensuring efficient resource allocation. In this paper, we analyze different C2TC configurations, leveraging multiple edge computing layers to optimize real-time application performance. We employ J-NECORA, an analytical tool designed to determine the optimal allocation of applications within C2TC at the design stage. Our findings demonstrate that the best allocation strategy depends on system-specific parameters, and J-NECORA effectively facilitates the comparison of different configurations, enabling informed decision-making.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1326908
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