Energy-Aware Adaptive Routing Solutions in IP-over-WDM Networks 2014-10-15¢  Aware Adaptive Routing

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  • Energy-Aware Adaptive Routing Solutions in IP-over-WDM Networks

    vorgelegt von Master of Science

    Filip Idzikowski

    von der Fakultät IV - Elektrotechnik und Informatik der Technischen Universität Berlin

    zur Erlangung des akademischen Grades

    Doktor der Ingenieurwissenschaften – Dr.-Ing. –

    genehmigte Dissertation

    Promotionsausschuss: Vorsitzender: Prof. Dr.-Ing. Hans-Joachim Grallert Gutachter: Prof. Dr.-Ing. Adam Wolisz Gutachter: Prof. Dr.-Ing. Andreas Kirstädter Gutachter: Prof. dr hab. inż. Wojciech Kabaciński

    Tag der wissenschaftlichen Aussprache: 30. Juni 2014

    Berlin 2014


  • Acknowledgements

    I explicitly use the personal pronoun “we” instead of “I” in this thesis in order to acknowledge all the people that I collaborated with and everybody who helped me throughout the work on this thesis.

    I express my gratitude to Prof. Adam Wolisz for hosting me at Telecommunications Networks Group (TKN) towards the successful PhD defense. My thesis would not be “round” without you, Prof. Wolisz! Thank you for your constructive comments. I am particularly grateful for initiating collaboration with Zuse Institut Berlin, which resulted in the ONDM2010 and the OSN2011 pa- pers. I thank very much Prof. Andreas Kirstädter and Prof. Wojciech Kabaciński, who evaluated my thesis at a high pace. Thank you for your comments which helped me improve the thesis.

    I discussed many, many issues about optical networking with Ahmad Rostami and Hagen Woes- ner. The topics often went beyond optical networks. Thanks a lot for your support, dear Ahmad and Hagen!

    The milestone papers (ONDM2010 and OSN2011 papers) would not be possible without Se- bastian Orlowski and Christian Raack! I learnt a lot from you guys! I will always be wondering how it was possible to do the nice piece of research without being supported by the same grant, project, action, etc.

    The time that I spent at TKN would not be the same without all the TKN-members. Berthold Rathke, Tobias Poschwatta and Marc Emmelmann provided inestimable support in the beginning of my stay in Berlin. Matthias Bohge and Daniel Willkomm provided motivation for thesis writing by organizing “TKN Graduiertenkolleg” and setting their examples. Sven Wiethölter, Jan-Hinrich Hauer and Osama Khader wrote their theses more or less in the same time period as I did. Thank you very much for the collaborative atmosphere and your hints!

    I shall never forget Łukasz Budzisz and Irina Piens and their tremendous support to my research. The numerous discussions tackled not only the research, but also the formalities of projects that I was involved in. Thank you very, very much!

    I thank also Murad Abusbaih, Konstantin Miller and Thomas Menzel for numerous discussions, friendly atmosphere and help in the organization of the PhD defense.

    I would like to acknowledge the students that I worked with at TKN, particularly Mickaël Guth and Francesco Portoso. I highly value your sincere engagement! The technical and formal issues were easier to solve thanks to Petra Hutt, Heike Klemz, Sonja Cecar, Angelika Kaminska, Sven Spuida, Jürgen Malinowski, Peter-René Shröter and Georgios Ainatzes. Thank you very much!

    I had the pleasure to collaborate with several international research groups throughout the years that I spent in Berlin. First, I would like to mention Fabio Neri, Marco Ajmone Marsan and Michela Meo for proposing and leading the TREND Network of Excellence (supported by the European Community’s Seventh Framework Programme FP7/2007-2013 under grant agreement n. 257740). Second, I want to explicitly thank the co-authors of the papers that contain main parts of this thesis, i.e., Edoardo Bonetto, Luca Chiaraviglio, Antonio Cianfrani, Angelo Coiro, Raul Duque, Felipe Jiménez, Esther Le Rouzic, Francesco Matera, Francesco Musumeci, Edion Tego,


  • Ward Van Heddeghem, Jorge López Vizcaı́no, and Yabin Ye. Thank you very much for the fruitful collaborations!

    Ahmad, Luca and Krzysztof Klimaszewski proof-read parts of my thesis. Ahmad, Łukasz, Mikołaj Chwalisz and Michael Döring listened to my rehearsals. Big thanks go to all of you for your time and valuable feedback!

    I thank also Henning Francke, Irene Hercka as well as Alicja and Adrian Fiedler for their help in the final stage of thesis writing.

    Last but not least, I want to thank my family. The process of upbringing and education is extremely challenging. I owe you a lot throughout the whole way towards my PhD, starting from my birth, through kindergarten, primary school, secondary school, graduate studies, and ending on my work at TKN. Thank you soooo, soooo much!

    Last but not least, I mention my beloved wife and children, who constantly supported me. I particularly felt it during the last months of the intensive work. I will always remember Ula’s words: “Ciiii, tatuś pisze doktorat!”1.

    1“Shush, daddy’s writing a PhD thesis!”


  • Abstract

    Today’s core networks are permanently powered on and consume non-negligible amount of en- ergy. Traffic varies over time giving an opportunity to switch off or put into standby mode a subset of network devices in order to save energy in low-demand hours. Line cards are targeted to be dy- namically switched on and off since their activation and deactivation times are expected to be suffi- ciently small, their power consumption is significant (400–500 W per line card), and a sufficiently large set of line cards is usually installed in the network. The focus of this thesis is on Energy- Aware Adaptive Routing Solutions (EA-ARSs) which utilize traffic variation, traffic rerouting and sleep modes in order to save energy consumed by line cards in Internet Protocol (IP)-over-Wave- length Division Multiplexing (WDM) networks.

    We collect from publicly available sources (product data sheets, research articles, and databases) extensive sets of realistic input data for the EA-ARSs that are crucial for energy saving, namely traffic data and power consumption data of single network devices. Extensive sets of traffic matri- ces containing traffic demands between all node pairs in the network cover periods of days, weeks, and months with granularity of 5 min, 15 min, a day, and a month. Physical supply topologies corresponding to the traffic matrices are reported too. The power consumption of single network devices determines the amount of power that can be saved in the whole network by switching off subsets of devices.

    Using the realistic input data we estimate the potential power and energy saving assuming diffe- rent levels of freedom of rerouting in an IP-over-WDM network. The proposed approaches Fixed Upper Fixed Lower (FUFL), Dynamic Upper Fixed Lower (DUFL) and Dynamic Upper Dynamic Lower (DUDL) differ with the possibility of rerouting of traffic demands over the logical (IP) to- pology, and the possibility of rerouting of lightpaths over the physical topology. A Static Base Network (SBN) is used as a starting point for EA-ARSs. The SBN determines devices installed in the network. Sophisticated Mixed-Integer Linear Programming (MILP) formulations are used for the SBN design as well as for DUFL and DUDL computations, which are highly complex optimization problems. FUFL is a simple, fully distributed heuristic. Our results show that flex- ibility of the IP routing (Dynamic Upper) contributes the most to the energy saving. Additional flexibility of routing in the WDM layer (Dynamic Lower) brings marginal savings. The simple approach FUFL brings significant savings, which are not as high as the savings brought by DUFL though. Furthermore, they depend on the ratio of the maximum total traffic demand and the capac- ity of a WDM channel. Spatial distribution of traffic demands also influences the energy savings achieved with FUFL.

    A set of evaluation criteria for EA-ARSs is proposed in order to determine the approaches which have a chance to be implemented in an operational network of the future. In this context, an adap- tive heuristic called Energy Watermark Algorithm (EWA) is proposed. EWA uses network con- figuration from previous time period in order to calculate new network configuration. This speeds up calculation of network configuration and reduces reconfiguration costs. Furthermore, EWA has a set of parameters, which allows a network operator to find the preferred trade-off between energy


  • Abstract

    saving and the Quality of Service (QoS) guarantees. EWA is compared with the Least Flow Algo- rithm (LFA) and the Genetic Algorithm (GA) taking power and energy consumption, reconfigured traffic, and overload ratio as evaluation metrics. The evaluation is performed on unique network scenarios. Differently to related research, past traffic data is used to design the SBN (determin- ing devices to be installed in the network and their configuration), and different future traffic data is used to evaluate EWA, LFA and GA starting from the SBN designed with a modified version of GA. EWA outperformed LFA and achieved results similar to the GA, having lower computa- tion times and smoother changes of power consumption. The overload is marginal, and observed mainly in the initial phase of the evaluation, when EWA could not use the network configuration from previous time period, but started from the overprovisioned configuration with all devices powered on.

    Implementation issues including control and management planes are discussed in this thesis as an outlook toward future work. FUFL and DUFL have been demonstrated on an IP-over-Gigabit Ethernet (GbE) testbed using off-the-shelf equipment. No traffic loss is