Alharbi, HA, El-Gorashi, TEH and Elmirghani, JMH (2016) Green Saudi National Fibre Network (SNFN). In: 4th Saudi International Conference on Information Technology (Big Data Analysis), KACSTIT 2016. KACSTIT 2016, 06-09 Nov 2016, Riyadh, Saudi Arabia. IEEE ISBN 9781467389563
Abstract
In 2015, there were more than 21 Million active users of the Internet in Saudi Arabia. In the present paper, we consider minimizing the power consumption of the Saudi National Fibre Network (SNFN) by formulating the problem as a mixed integer linear programming (MILP) model. Firstly, we optimize the location of single or multiple data centres in the SNFN under a traffic profile based on a gravity model where the production rate and attractiveness of each node is proportional to the population of that node. We evaluate the network power consumption considering three scenarios of data centre locations. The MILP model results show that identifying the optimum data centre locations can save up to 53% of the network power consumption compared to the random data centre locations. Secondly, we optimize the SNFN physical topology considering different data centers locations. Moreover, the model results show that optimizing the network physical topology can save up to 76% of the total power consumption compared to the current topology.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016, 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. |
Keywords: | Power demand, IP networks, Data models, Optical fibers, Topology, Network topology, WDM networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Feb 2017 15:00 |
Last Modified: | 27 Jan 2018 20:51 |
Published Version: | https://doi.org/10.1109/KACSTIT.2016.7756071 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/KACSTIT.2016.7756071 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:111898 |