In recent years, the development of the Internet of Things (IoT) has largely been supported by the parallel development of the Cloud computing capacities. Cloud computing offered elastic and on-demand computing power able to host and support crucial IoT functions. However, the proliferation of connected objects poses the problem of the confidentiality of the data produced. This proliferation also threatens the performances of the supporting networks. To tackle those problems, the research community has recently turned to Fog Computing. In this paper, we present CIoud4IoT, a platform able to perform horizontal (roaming) and vertical (offloading) migration of IoT functions. We implement our demonstration using a Kubernetes cIuster organised in three tiers: Cloud, Edge and IoT gateways. Our first use cases shows how IoT function roaming can be used in the context of health care data exploitation. The second use case exploits the IoT offloading capacity of our platform to optimize the remote diagnostic of mechanical engines.

Edge computing in IoT context: horizontal and vertical Linux container migration

Dupont, Corentin;Giaffreda, Raffaele;Capra, Luca
2017-01-01

Abstract

In recent years, the development of the Internet of Things (IoT) has largely been supported by the parallel development of the Cloud computing capacities. Cloud computing offered elastic and on-demand computing power able to host and support crucial IoT functions. However, the proliferation of connected objects poses the problem of the confidentiality of the data produced. This proliferation also threatens the performances of the supporting networks. To tackle those problems, the research community has recently turned to Fog Computing. In this paper, we present CIoud4IoT, a platform able to perform horizontal (roaming) and vertical (offloading) migration of IoT functions. We implement our demonstration using a Kubernetes cIuster organised in three tiers: Cloud, Edge and IoT gateways. Our first use cases shows how IoT function roaming can be used in the context of health care data exploitation. The second use case exploits the IoT offloading capacity of our platform to optimize the remote diagnostic of mechanical engines.
2017
978-1-5090-5873-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/311454
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