Abstract
The need for minimizing power consumption has long been an important consideration in wireless networks. In recent years, there has been a growing recognition of the need for developing energy efficient network design approaches for WDM backbone networks as well. The typical approach has been to switch off some components such as line cards and router ports during low demand periods and has focussed on traditional static and dynamic traffic models. In this paper, we propose a new approach that exploits knowledge of demand holding times to intelligently share resources among non-overlapping demands and reduce the overall power consumption of the network. We consider both the fixed window and sliding window scheduled traffic models, and present (i) a set of comprehensive integer linear program formulations and (ii) a novel Genetic Algorithm (GA)-based strategy that jointly minimizes both power consumption and transceiver cost for the logical topology. The proposed approaches are used to determine the best route and time slot (for sliding window) for each demand and lead to significant improvements in terms of power consumption compared to existing techniques.
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The work of A. Jaekel has been supported in part by research Grants from the Natural Sciences and Engineering Research Council of Canada (NSERC).
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Jaekel, A., Pare, J., Chen, Y. et al. Traffic grooming of scheduled demands for minimizing energy consumption. Photon Netw Commun 29, 151–163 (2015). https://doi.org/10.1007/s11107-014-0478-7
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DOI: https://doi.org/10.1007/s11107-014-0478-7