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A Time-Predictable Fog-Integrated Cloud Framework: One Step Forward in the Deployment of a Smart Factory

Authors:


Publication Type:

Conference/Workshop Paper

Venue:

CSI International Symposium on Real-Time and Embedded Systems and Technologies

DOI:

10.1109/RTEST.2018.8397079


Abstract

This paper highlights cloud computing as one of the principal building blocks of a smart factory, providing a huge data storage space and a highly scalable computational capacity. The cloud computing system used in a smart factory should be time-predictable to be able to satisfy hard real-time requirements of various applications existing in manufacturing systems. Interleaving an intermediate computing layer-called fog-between the factory and the cloud data center is a promising solution to deal with latency requirements of hard real-time applications. In this paper, a time-predictable cloud framework is proposed which is able to satisfy end-to-end latency requirements in a smart factory. To propose such an industrial cloud framework, we not only use existing real-time technologies such as Industrial Ethernet and the Real-time XEN hypervisor, but we also discuss unaddressed challenges. Among the unaddressed challenges, the partitioning of a given workload between the fog and the cloud is targeted. Addressing the partitioning problem not only provides a resource provisioning mechanism, but it also gives us a prominent design decision specifying how much computing resource is required to develop the fog platform, and how large should the minimum communication bandwidth be between the fog and the cloud data center.

Bibtex

@inproceedings{Faragardi5019,
author = {Hamid Reza Faragardi and Saed Dehnavi and Mehdi Kargahi and Alessandro Papadopoulos and Thomas Nolte},
title = {A Time-Predictable Fog-Integrated Cloud Framework: One Step Forward in the Deployment of a Smart Factory},
pages = {54--62},
month = {May},
year = {2018},
booktitle = {CSI International Symposium on Real-Time and Embedded Systems and Technologies },
url = {http://www.es.mdh.se/publications/5019-}
}