Green Energy Optimization Of Optical Network Design

As Internet energy consumption has proliferated in recent years, its sustainabilitywill face huge challenges. How to improve the energy efficiency of the Internet hasbecome an important scientific question that needs to be addressed in the near future.The energy consumption of optical network, which is one of the most important partsof the Internet, is attracting more and more attentions.This thesis focuses on the issue of energy-saving in the backbone opticaltransport network. Based on the assumption of modular router cards, we designenergy-minimized IP over WDM networks by jointly applying the lightpath bypassand router-card sleeping strategies, which is different from the traditional routerport-based sleeping strategy. The designed networks can significantly reduce energyconsumption, up to40%compared to the non-sleeping case. In addition, to reduceGreen House Gas (GHG) emissions of IP over WDM networks, we propose tomaximize renewable energy usage at each network node so as to reduce theconsumption of non-renewable energy. A “Follow the Sun, Follow the Wind”(FTSFTW) strategy is proposed for the IP over WDM network to periodicallyreconfigure the lightpath virtual topology to enable more lightpaths to start or end atnodes where maximum renewable energy is available. The simulation results indicatethat the proposed FTSFTW strategy can save up to75%or more non-renewableenergy in the considered example scenarios compared with the traditional pureenergy-minimized design approach. Finally, a common approach for achieving highenergy efficiency is to selectively turn off (or sleep) network devices. However, thisstrategy can create problems of network survivability and security if all the networkdevices were turned off by a hacker. We configure a mixture of sleep-enabled andnon-sleep-enabled router cards at each node to design a green IP over WDM networkwhich can ensure network survivability and security and meanwhile maximally saveenergy consumption. Simulation results based on some test networks show that theproposed approach can save up to28%energy consumption.