Modeling and optimization of data center location and routing and spectrum allocation in survivable elastic optical networks

Abstract In this paper, we focus on the problem of locating data centers (DCs) and routing traffic demands in survivable elastic optical network (EON). We consider and compare two different modeling and optimization approaches: joint optimization of both issues at the same time (problem DC-RSA) and decomposition method, which divides problem into two subsequent subproblems of DC location and demands routing with a given DC locations. For both approaches we formulate integer linear programming (ILP) models and propose heuristic algorithms to solve related problem instances. In case of the decomposition method, we propose to use topology-based (that follows directly from the network graph structure) and demographic-economical (characteristics of the cities that correspond to network nodes) data to define DC location policies. We define seven different DC location polices, which can be classified as topology-based, demographic-economical, and hybrid (use both groups of information). Next, we perform extensive numerical experiments on realistic network topologies, in order to evaluate efficiency of the proposed optimization methods and compare different optimization approaches in terms of the computational complexity, spectrum usage, and survivability provisioning in case of a random large-scale disaster. The results of our investigation show that the joint optimization problem (DC-RSA) is much more complex than the decomposition approach. However, the corresponding results bring better network performance according to the spectrum usage and provide good level of network survivability at the same time. Regarding different DC location policies applied with decomposition method, the investigation proves that DC location policy has a crucial influence on the network performance (in terms of the spectrum usage and survivability provisioning), especially when the number of available DCs is relatively small. According to the results, topology-based DC location policies significantly outperform demographic-economical methods in terms of both—spectrum usage and survivability provisioning.

[1]  Helio Waldman,et al.  MILP formulation for squeezed protection in Spectrum-Sliced Elastic Optical Path Networks , 2012, 2012 International Symposium on Performance Evaluation of Computer & Telecommunication Systems (SPECTS).

[2]  Krzysztof Walkowiak,et al.  Distance-adaptive transmission in cloud-ready elastic optical networks , 2014, IEEE/OSA Journal of Optical Communications and Networking.

[3]  Seyed Jalal Jafari,et al.  GeoIP clustering: Solving replica server placement problem in content delivery networks by clustering users according to their physical locations , 2013, The 5th Conference on Information and Knowledge Technology.

[4]  Krzysztof Walkowiak,et al.  On the advantages of elastic optical networks for provisioning of cloud computing traffic , 2013, IEEE Network.

[5]  Krzysztof Walkowiak,et al.  Comparison of different data center location policies in survivable elastic optical networks , 2015, 2015 7th International Workshop on Reliable Networks Design and Modeling (RNDM).

[6]  Miroslaw Klinkowski,et al.  AN EVOLUTIONARY ALGORITHM APPROACH FOR DEDICATED PATH PROTECTION PROBLEM IN ELASTIC OPTICAL NETWORKS , 2013, Cybern. Syst..

[7]  B. Jaumard,et al.  Selecting the best locations for data centers in resilient optical grid/cloud dimensioning , 2012, 2012 14th International Conference on Transparent Optical Networks (ICTON).

[8]  JinnoMasahiko,et al.  Spectrum-efficient and scalable elastic optical path network , 2009 .

[9]  Yuefeng Ji,et al.  Data center service localization based on virtual resource migration in software defined elastic optical network , 2015, 2015 Optical Fiber Communications Conference and Exhibition (OFC).

[10]  Biswanath Mukherjee,et al.  Disaster-aware data-center and content placement in cloud networks , 2013, 2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).

[11]  Ioannis Tomkos,et al.  Elastic Bandwidth Allocation in Flexible OFDM-Based Optical Networks (vol 29, pg 1354, 2011) , 2011 .

[12]  Y Sone,et al.  Bandwidth Squeezed Restoration in Spectrum-Sliced Elastic Optical Path Networks (SLICE) , 2011, IEEE/OSA Journal of Optical Communications and Networking.

[13]  Krzysztof Walkowiak,et al.  On Minimization of the Spectrum Usage in Elastic Optical Networks with Joint Unicast and Anycast Traffic , 2013 .

[14]  J. P. Fernandez-Palacios,et al.  Dynamic operation of flexi-grid OFDM-based networks , 2012, OFC/NFOEC.

[15]  Marc Ruiz,et al.  Solving Routing and Spectrum Allocation Related Optimization Problems: From Off-Line to In-Operation Flexgrid Network Planning , 2014 .

[16]  M. Jinno,et al.  Algorithms for maximizing spectrum efficiency in elastic optical path networks that adopt distance adaptive modulation , 2010, 36th European Conference and Exhibition on Optical Communication.

[17]  Zuqing Zhu,et al.  Dynamic anycast in inter-datacenter networks over elastic optical infrastructure , 2014, 2014 International Conference on Computing, Networking and Communications (ICNC).

[18]  Albert Y. Zomaya,et al.  Effects of Replica Placement Algorithms on Performance of structured Overlay Networks , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[19]  L. Velasco,et al.  Solving Routing and Spectrum Allocation Related Optimization Problems: From Off-Line to In-Operation Flexgrid Network Planning , 2013, Journal of Lightwave Technology.

[20]  Balagangadhar G. Bathula,et al.  Crosstalk-aware anycast routing and wavelength assignment in optical WDM networks , 2010, 2010 IEEE 4th International Symposium on Advanced Networks and Telecommunication Systems.

[21]  James P. G. Sterbenz,et al.  Modelling communication network challenges for Future Internet resilience, survivability, and disruption tolerance: a simulation-based approach , 2013, Telecommun. Syst..

[22]  Chris Develder,et al.  Anycast end-to-end resilience for cloud services over virtual optical networks , 2013, 2013 15th International Conference on Transparent Optical Networks (ICTON).

[23]  Xin Sun,et al.  An Efficient Replica Location Method in Hierarchical P2P Networks , 2009, 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science.

[24]  Jacek Rak,et al.  Protection in elastic optical networks , 2015, IEEE Network.

[25]  Pin-Han Ho,et al.  Data center network placement and service protection in all-optical mesh networks , 2013, 2013 9th International Conference on the Design of Reliable Communication Networks (DRCN).

[26]  Xiaojun Cao,et al.  Routing and Spectrum Allocation in Spectrum-Sliced Elastic Optical Path Networks , 2011, 2011 IEEE International Conference on Communications (ICC).

[27]  K ÇetinkayaEgemen,et al.  Modelling communication network challenges for Future Internet resilience, survivability, and disruption tolerance , 2013 .

[28]  Yuefeng Ji,et al.  CSO: cross stratum optimization for optical as a service , 2015, IEEE Communications Magazine.

[29]  J. Y. Yen Finding the K Shortest Loopless Paths in a Network , 1971 .

[30]  Deep Medhi,et al.  Routing, flow, and capacity design in communication and computer networks , 2004 .

[31]  Biswanath Mukherjee,et al.  Survivable traffic grooming in elastic optical networks — Shared path protection , 2012, 2012 IEEE International Conference on Communications (ICC).

[32]  Brunilde Sansò,et al.  A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks , 2013, IEEE Transactions on Cloud Computing.

[33]  Miroslaw Klinkowski,et al.  ILP modelling and joint optimization of anycast and unicast traffic in survivable elastic optical networks , 2016, Electron. Notes Discret. Math..

[34]  Krzysztof Walkowiak,et al.  Anycasting in connection-oriented computer networks: Models, algorithms and results , 2010, Int. J. Appl. Math. Comput. Sci..

[35]  Masahiko Jinno,et al.  Spectrum-efficient and scalable elastic optical path network: architecture, benefits, and enabling technologies , 2009, IEEE Communications Magazine.

[36]  Marc Ruiz,et al.  Modeling the routing and spectrum allocation problem for flexgrid optical networks , 2012, Photonic Network Communications.

[37]  Krzysztof Walkowiak,et al.  Shared backup path protection in elastic optical networks: Modeling and optimization , 2013, 2013 9th International Conference on the Design of Reliable Communication Networks (DRCN).

[38]  Xiaowen Dong,et al.  Green IP Over WDM Networks With Data Centers , 2011, Journal of Lightwave Technology.

[39]  Deep Medhi,et al.  Time-varying resilient virtual network mapping for multi-location cloud data centers , 2014, 2014 16th International Conference on Transparent Optical Networks (ICTON).

[40]  Krzysztof Walkowiak,et al.  Optimization algorithms for data center location problem in Elastic Optical Networks , 2013, 2013 15th International Conference on Transparent Optical Networks (ICTON).

[41]  Chris Develder,et al.  Improving energy efficiency in optical cloud networks by exploiting anycast routing , 2011, 2011 Asia Communications and Photonics Conference and Exhibition (ACP).

[42]  B. Jaumard,et al.  Anycast Routing for Survivable Optical Grids: Scalable Solution Methods and the Impact of Relocation , 2011, IEEE/OSA Journal of Optical Communications and Networking.

[43]  Krzysztof Walkowiak,et al.  Joint anycast and unicast routing and spectrum allocation with dedicated path protection in Elastic Optical Networks , 2014, 2014 10th International Conference on the Design of Reliable Communication Networks (DRCN).

[44]  J. Y. Yen An algorithm for finding shortest routes from all source nodes to a given destination in general networks , 1970 .