Impact of the Net Neutrality Repeal on Communication Networks: Conclusions & References

Written by netneutrality | Published 2024/04/11
Tech Story Tags: net-neutrality | isps | communication-networks | techno-economic-model | milp | cloud-fog-architectures | internet | internet-traffic

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This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Hatem A. Alharbi, CSchool of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom;

(2) Taisir E.H. Elgorashi, School of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom;

(3) Jaafar M.H. Elmirghani, School of Electronic and Electrical Engineering, University of Leeds, LS2 9JT, United Kingdom.

Table of Links

Abstract & Introduction

Related Works

Repealing Net Neutrality

Profit-Driven Model Results

Conclusions & References

Biographies

V. CONCLUSIONS

In this paper, we developed a MILP model to optimize the pricing scheme used by ISPs to charge CPs for delivering their video content under the repeal of net neutrality where ISPs can treat data intensive traffic less favorably. A techno-economic Mixed Integer Linear Programming (MILP) model is developed to maximize the ISP profit by optimizing the ISP pricing scheme to charge different classes of service differently subject to PED. We considered three classes of service that represent different data rate requirements of video content. The analysis addressed three CP delivery scenarios; cloud-based delivery, cloud-fog based delivery and fog-based delivery. The results show that the discriminatory pricing scheme can increase the ISPs profit by a factor of 8. The results also show that by influencing the way end-users consume data-intensive content, the core network traffic and consequently power consumption are reduced by up to 49% and 55%, respectively, compared to the net neutrality scenario.

Acknowledgements

The authors would like to acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC), INTERNET (EP/H040536/1), STAR (EP/K016873/1) and TOWS (EP/S016570/1) projects. The first author would like to acknowledge the Government of Saudi Arabia and Taibah University for funding his PhD scholarship. All data are provided in full in the results section of this paper.

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Published by HackerNoon on 2024/04/11