Energy-Aware Routing in Multiple Domains Software-Defined Networks
Abstract The growing energy consumption of communication networks has attracted the attention of the networking researchers in the last decade. In this context, the new architecture of Software-Defined Networks (SDN) allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale SDN with multiple domains. The solution proposed, called DEAR (Distributed Energy-Aware Routing), tackles the problem of minimizing the number of links that can be used to satisfy a given data traffic demand under performance constraints such as control traffic delay and link utilization. To this end, we present a complete formulation of the optimization problem that considers routing requirements for control and data plane communications. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.
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Wang, R., Jiang, Z., Gao, S., Yang, W., Xia, Y., and Zhu, M., 2014. Energy-Aware Routing Algorithms in Software-Defined Networks. In Proc. IEEE WoWMoM'14, pages 1–6.
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Zhang, M., Yi, C., Liu, B., and Zhang, B., 2010. GreenTE: Power-Aware Traffic Engineering. In Proc. IEEE. https://doi.org/10.1109/icnp.2010.5762751
Zhang, Y., 2004. Abilene TM. http://www.cs.utexas.edu/~yzhang/research/AbileneTM/. Last accessed on January 20, 2016.
Gelenbe, E. and Caseau, Y., 2015. The Impact of Information Technology on Energy Consumption and Carbon Emissions. ACM Ubiquity, 2015(June):1–15.
Giroire, F., Moulierac, J., and Phan, T. K., 2014. Optimizing Rule Placement in Software-Defined Networks for Energy-Aware Routing. In Proc. IEEE GLOBECOM'14, pages 2523–2529. https://doi.org/10.1109/glocom.2014.7037187
Gupta, M. and Singh, S., 2003. Greening of the Internet. In Proc. ACM SIGCOMM'03, pages 19–26. https://doi.org/10.1145/863955.863959
Gurobi Optimization. Version 6.5. http://www.gurobi.com/. Last accessed on May 16, 2016.
Heller, B., Sherwood, R., and McKeown, N., 2012. The Controller Placement Problem. In Proc. HotSDN'12, pages 7–12. https://doi.org/10.1145/2342441.2342444
Kreutz, D., Ramos, F. M. V., Veríssimo, P. E., Rothenberg, C. E., Azodolmolky, S., and Uhlig, S., 2015. Software-Defined Networking: A Comprehensive Survey. Proceedings of the IEEE, 103:14–76. https://doi.org/10.1109/JPROC.2014.2371999
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., and Turner, J., 2008. OpenFlow:Enabling Innovation in Campus Networks. ACM SIGCOMM Computer Communication Review, 38(2):69–74. https://doi.org/10.1145/1355734.1355746
Sharma, S., Staessens, D., Colle, D., Pickavet, M., and Demeester, P., 2013. Automatic Bootstrapping of… https://doi.org/10.1109/lanman.2013.6528283
The Climate Group, 2008. SMART 2020 Report, Enabling the Low Carbon Economy in the Information Age.
Van Heddeghem, W., Lambert, S., Lannoo, B., Colle, D., Pickavet, M., and Demeester, P., 2014. Trends in Worldwide ICT Electricity Consumption from 2007 to 2012. Computer Communications, 50:64–76. https://doi.org/10.1016/j.comcom.2014.02.008
Wang, H., Li, Y., Jin, D., Hui, P., and Wu, J., 2016. Saving Energy in Partially Deployed Software Defined Networks. IEEE Transactions on Computers, 65(5):1578–1592.
https://doi.org/10.1109/TC.2015.2451662
Wang, R., Jiang, Z., Gao, S., Yang, W., Xia, Y., and Zhu, M., 2014. Energy-Aware Routing Algorithms in Software-Defined Networks. In Proc. IEEE WoWMoM'14, pages 1–6.
https://doi.org/10.1109/wowmom.2014.6918982
Zhang, M., Yi, C., Liu, B., and Zhang, B., 2010. GreenTE: Power-Aware Traffic Engineering. In Proc. IEEE. https://doi.org/10.1109/icnp.2010.5762751
Zhang, Y., 2004. Abilene TM. http://www.cs.utexas.edu/~yzhang/research/AbileneTM/. Last accessed on January 20, 2016.
Fernández-Fernández, A., Cervelló-Pastor, C., & Ochoa-Aday, L. (2016). Energy-Aware Routing in Multiple Domains Software-Defined Networks. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 5(3), 13–19. https://doi.org/10.14201/ADCAIJ2016531319
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