Journal of Lightwave Technology | VOL. 32
Read

“Follow the Sun, Follow the Wind” Lightpath Virtual Topology Reconfiguration in IP Over WDM Network

Publication Date Jun 1, 2014

Abstract

Green House Gas (GHG) emissions mainly come from the consumption of non-renewable energy. To reduce GHG emissions of IP over WDM networks, we propose to maximize renewable energy usage at each network node location so as to reduce the consumption of non-renewable energy. A “Follow the Sun, Follow the Wind” strategy is proposed for the IP over WDM network to periodically reconfigure the lightpath virtual topology to enable more lightpaths to start or end at nodes where maximum renewable energy is available. We develop a mixed integer linear programming model to design new lightpath virtual topologies. Since the computational complexity of the optimization model is excessive, we also propose a simple but efficient heuristic algorithm to tackle this. Our results indicate that a network operated in this way can significantly reduce non-renewable energy consumption as illustrated in the example network scenarios considered.

Concepts

Consumption Of Non-renewable Energy Maximum Renewable Energy Mixed Integer Linear Programming Model Network Node Location Green House Gas Emissions WDM Network Network Scenarios Green House Gas Consumption Of Energy Simple Heuristic Algorithm

Round-ups are the summaries of handpicked papers around trending topics published every week. These would enable you to scan through a collection of papers and decide if the paper is relevant to you before actually investing time into reading it.

Climate change Research Articles published between Jan 23, 2023 to Jan 29, 2023

R DiscoveryJan 30, 2023
R DiscoveryArticles Included:  3

Climate change adaptation has shifted from a single-dimension to an integrative approach that aligns with vulnerability and resilience concepts. Adapt...

Read More

Coronavirus Pandemic

You can also read COVID related content on R COVID-19

R ProductsCOVID-19

ONE PROBLEM . ONE PURPOSE . ONE PLACE

Creating the world’s largest AI-driven & human-curated collection of research, news, expert recommendations and educational resources on COVID-19

COVID-19 Dashboard

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on “as is” basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The Copyright Law.