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arXiv · 2401.14968

Atmosphere: Context and situational-aware collaborative IoT architecture for edge-fog-cloud computing

Guadalupe Ortiz·Meftah Zouai·Okba Kazar·Alfonso Garcia-de-Prado·Juan Boubeta-Puig
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Abstract

The Internet of Things (IoT) has grown significantly in popularity, accompanied by increased capacity and lower cost of communications, and overwhelming development of technologies. At the same time, big data and real-time data analysis have taken on great importance and have been accompanied by unprecedented interest in sharing data among citizens, public administrations and other organisms, giving rise to what is known as the Collaborative Internet of Things. This growth in data and infrastructure must be accompanied by a software architecture that allows its exploitation. Although there are various proposals focused on the exploitation of the IoT at edge, fog and/or cloud levels, it is not easy to find a software solution that exploits the three tiers together, taking maximum advantage not only of the analysis of contextual and situational data at each tier, but also of two-way communications between adjacent ones. In this paper, we propose an architecture that solves these deficiencies by proposing novel technologies which are appropriate for managing the resources of each tier: edge, fog and cloud. In addition, the fact that two-way communications along the three tiers of the architecture is allowed considerably enriches the contextual and situational information in each layer, and substantially assists decision making in real time. The paper illustrates the proposed software architecture through a case study of respiratory disease surveillance in hospitals. As a result, the proposed architecture permits efficient communications between the different tiers responding to the needs of these types of IoT scenarios.

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Guadalupe Ortiz, Meftah Zouai, Okba Kazar, Alfonso Garcia-de-Prado, Juan Boubeta-Puig. 2024-01-26. Atmosphere: Context and situational-aware collaborative IoT architecture for edge-fog-cloud computing. https://doi.org/10.1016/j.csi.2021.103550

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