Abstract

As networks continue to expand, energy consumption is increasingly becoming a major issue, affecting not only the operational costs, but also the associated emission of greenhouse gasses (GHG). Thus, reducing power consumption, as well as GHGs (primarily CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) to reduce the carbon footprint of the network, has started to play a significant role in network planning. In networks with both renewable and non-renewable power sources, minimizing only the overall power consumption without considering the associated CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> levels emitted by individual nodes can lead to unnecessarily high levels of GHG emissions. Conversely, strictly minimizing GHG emission by avoiding non-renewable power sources may lead to longer routes with significantly increased overall power consumption (higher operational costs) which is not very attractive to operators. In this paper, we present a hybrid approach for green routing and wavelength assignment (RWA) in backbone optical networks which reduces both criteria, searching for an advantageous trade-off between costs and environmental-friendliness. An integer linear programming (ILP) formulation for the problem is proposed which minimizes the overall energy consumption as well as the total GHGs emitted, scaled by a tunable penalty factor. GHG emissions are calculated according to GHG-conversion factors of individual nodes representing the amount of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emitted per kWh of energy consumed. Results indicate that advantageous trade-offs can be achieved by selecting appropriate penalty factor values which yield RWA solutions with low power consumption, GHG emissions, and, additionally, lower costs of the associated electric bill.

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