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Fog computing framework for internet of things applications

Al-Khafajiy, M., Baker, T., Al-Libawy, H., Waraich, A., Chalmers, C. and Alfandi, O. (2018) Fog computing framework for internet of things applications. In: 11th International Conference on Developments in eSystems Engineering (DeSE), 02-05 Sep 2018, Cambridge, UK, pp. 71-77, https://doi.org/10.1109/DeSE.2018.00017.

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To link to this item DOI: 10.1109/DeSE.2018.00017

Abstract/Summary

Within the Internet of Things (IoT) era, a big volume of data is generated/gathered every second from billions of connected devices. The current network paradigm, which relies on centralised data centres (a.k.a. Cloud computing), becomes impractical solution for IoT data storing and processing due to the long distance between the data source (e.g., sensors) and designated data centres. In other words, by the time the data reaches a far data centre, the importance of the data would be vanished. Therefore, the network topologies have been evolved to permit data processing and storage at the edge of the network, introducing what so-called "Fog computing". The later will obviously lead to improvements in quality of service (QoS) via processing and responding quickly and efficiently to varieties of data processing requests. Therefore, understanding Fog computing architecture and its role in improving QoS is a paramount research topic. In this research, we are proposing a Fog computing architecture and framework to improve QoS for IoT applications. Proposed system supports cooperation among Fog nodes in a given location, in order to permit data processing in a shared mode, hence satisfies QoS and serves largest number of service requests. The proposed framework could have the potential in achieving sustainable network paradigm and highlights significant benefits of Fog computing into the computing ecosystem.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:88470

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