Bozorgchenani, A. orcid.org/0000-0003-1360-6952, Tarchi, D. and Corazza, G.E. (2018) A control and data plane split approach for partial offloading in mobile fog networks. In: Proceedings of 2018 IEEE Wireless Communications and Networking Conference (WCNC). 2018 IEEE Wireless Communications and Networking Conference (WCNC), 15-18 Apr 2018, Barcelona, Spain. IEEE ISBN 9781538617342
Abstract
Fog Computing offers storage and computational capabilities to the edge devices by reducing the traffic at the fronthaul. A fog environment can be seen as composed by two main classes of devices, Fog Nodes (FNs) and Fog-Access Points (F-APs). At the same time, one of the major advances in 5G systems is decoupling the control and the data planes. With this in mind we are here proposing an optimization technique for a mobile environment where the Device to Device (D2D) communications between FNs act as a control plane for aiding the computational offloading traffic operating on the data plane composed by the FN - F-AP links. Interactions in the FNs layer are used for exchanging the information about the status of the F-AP to be exploited for offloading the computation. With this knowledge, we have considered the mobility of FNs and the F-APs' coverage areas to propose a partial offloading approach where the amount of tasks to be offloaded is estimated while the FNs are still within the coverage of their F-APs. Numerical results show that the proposed approaches allow to achieve performance closer to the ideal case, by reducing the data loss and the delay.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Task analysis, Device-to-device communication, Delays, Edge computing, Computer architecture, Conferences, Wireless communication |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Dec 2023 16:11 |
Last Modified: | 11 Dec 2023 16:11 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/wcnc.2018.8377170 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201536 |