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Towards Trusted and Accountable Win-Win SDWN Platform for Trading Wi-Fi Network Access

Hashem Eiza, M, Raschella, A, MacKay, M, Shi, Q and Bouhafs, F (2023) Towards Trusted and Accountable Win-Win SDWN Platform for Trading Wi-Fi Network Access. In: 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC) . (IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA.).

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Wi-Fi is still by far the most common and cheapest wireless technology to deliver Internet services to users and digital devices, which are dramatically increasing in terms of quantity and the quality of services they require. As a result, Wi-Fi networks are the most congested wireless technology. This issue incentivised many researchers to propose radio resource management solutions in unlicensed frequency bands to alleviate that problem. Nonetheless, these solutions lack coordination among the network operators who utilise wireless spectrum and hence, they do not efficiently solve the problem. In this work we propose a ‘win-win’ platform based on Software Defined Wireless Networking (SDWN) that facilitates a trusted and accountable WiFi network access trading among networks operators, to solve the congestion problem in a collaborative manner that is beneficial for everyone. The platform enables Wi-Fi networks operators to both improve their users’ satisfaction and earn incentives hence, achieving the ‘win-win’ equilibrium. Evaluation results in a dense Wi-Fi network environment show how the ‘win-win’ platform significantly improves satisfaction and achieved data rates for the cooperating networks operators’ users in comparison to the standard approach.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science & Mathematics
Publisher: IEEE
SWORD Depositor: A Symplectic
Date Deposited: 13 Dec 2022 12:23
Last Modified: 21 Mar 2023 12:26
DOI or ID number: 10.1109/CCNC51644.2023.10060540
URI: https://researchonline.ljmu.ac.uk/id/eprint/18383
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