Quality of service provisioning and energy minimized scheduling in software defined flexible optical networks

The over-provisioning of capacities in optical networks is not a sustainable approach in the long run. In this paper, we propose a software defined networking scheme for quality of service provisioning through energy efficient assignment of optical transponders, employing bandwidth variable distance adaptive modulation and coding. Our scheme enables avoiding over-provisioning of transponder capacity as well as short-term major changes in equipment allocation for networks with dynamic traffic. We make use of the seasonal auto-regressive integrated moving average model to forecast the statistics of network traffic for an arbitrary time span based on the requirements and the constraints of the service provider. The quality of service measure is defined as the probability of congestion at the core router ports. A stochastic linear programming approach is used to provide a solution for energy efficient assignment of optical transponders and electronic switching capacity while ensuring a certain level of quality of service to core routers. The scheduling of optical lightpath capacities is performed for the entire duration of time under consideration, whereas the scheduling of electronic switching capacities is performed based on the short-term dynamics of the traffic. Numerical results show up to 48% improvement in the energy efficiency of optical networks and 45% reduction in the number of optical lightpaths through the implementation of the proposed technique, compared to a design based on employing conventional fixed optical transponders and no traffic rerouting, where both schemes satisfy the congestion probability requirements.

[1]  Adam Wolisz,et al.  Dynamic routing at different layers in IP-over-WDM networks - Maximizing energy savings , 2011, Opt. Switch. Netw..

[2]  Ting Wang,et al.  On the Design of Energy-Efficient Mixed-Line-Rate (MLR) Optical Networks , 2012, Journal of Lightwave Technology.

[3]  P. Phillips,et al.  Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? , 1992 .

[4]  Idelfonso Tafur Monroy,et al.  Energy efficiency analysis for flexible-grid OFDM-based optical networks , 2012, Comput. Networks.

[5]  Charu C. Aggarwal,et al.  Diagnosing infeasibilities in network flow problems , 1998, Math. Program..

[6]  R.S. Tucker,et al.  Evolution of WDM Optical IP Networks: A Cost and Energy Perspective , 2009, Journal of Lightwave Technology.

[7]  Amarnath Mukherjee,et al.  Time series models for internet traffic , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[8]  Olivier Bonaventure,et al.  Achieving sub-second IGP convergence in large IP networks , 2005, CCRV.

[9]  W. Shieh,et al.  On the Energy Efficiency of Modulation Formats for Optical Communications , 2013, IEEE Photonics Technology Letters.

[10]  Xi Chen,et al.  Information Spectral Efficiency and Launch Power Density Limits Due to Fiber Nonlinearity for Coherent Optical OFDM Systems , 2011, IEEE Photonics Journal.

[11]  Joel J. P. C. Rodrigues,et al.  A Study of Energy-Aware Traffic Grooming in Optical Networks: Static and Dynamic Cases , 2013, IEEE Systems Journal.

[12]  Chunming Qiao,et al.  A predictive and incremental grooming scheme for time-varying traffic in WDM networks , 2013, 2013 Proceedings IEEE INFOCOM.

[13]  Masahiko Jinno,et al.  Elastic optical networking: a new dawn for the optical layer? , 2012, IEEE Communications Magazine.

[14]  Jaafar M. H. Elmirghani,et al.  Green optical orthogonal frequency-division multiplexing networks , 2014 .

[15]  William Shieh,et al.  Power-efficiency considerations for adaptive long-haul optical transceivers , 2014, IEEE/OSA Journal of Optical Communications and Networking.

[16]  P. Young,et al.  Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.

[17]  William Shieh,et al.  Flexible Optical Networks: An Energy Efficiency Perspective , 2014, Journal of Lightwave Technology.

[18]  Jennifer Ryan,et al.  Finding the minimum weight IIS cover of an infeasible system of linear inequalities , 1996, Annals of Mathematics and Artificial Intelligence.

[19]  S. Aleksic Electrical power consumption of large electronic and optical switching fabrics , 2010, 2010 IEEE Photonics Society Winter Topicals Meeting Series (WTM).

[20]  E.B. Desurvire,et al.  Capacity Demand and Technology Challenges for Lightwave Systems in the Next Two Decades , 2006, Journal of Lightwave Technology.

[21]  Massimo Tornatore,et al.  Optical network design with mixed line rates , 2009, Opt. Switch. Netw..

[22]  Dong Shen,et al.  Energy-Efficient Traffic Grooming in WDM Networks With Scheduled Time Traffic , 2011, Journal of Lightwave Technology.

[23]  Michalis Faloutsos,et al.  A nonstationary Poisson view of Internet traffic , 2004, IEEE INFOCOM 2004.

[24]  Nick McKeown,et al.  Part I: buffer sizes for core routers , 2005, CCRV.