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Traffic Matrix Estimation for IP-over-WDM Networks via Optical Bypass Techniques

Traffic Matrix Estimation for IP-over-WDM Networks via Optical Bypass Techniques
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摘要 A traffic matrix is a necessary parameter fornetwork management functions,and itsupplies a flow-level view of a largescale IP-over-WDM backbone network.This paper studies the problem of traffic matrix estimationand proposes an exact traffic matrix estimation approach based on network tomography techniques.The traditional network tomography model is extended to make it compatible with compressive sensing constraints.First,a stochastic perturbation is introduced in the traditional network tomography inference model.Then,an algorithm is proposed to achieve additional optical link observations via optical bypass techniques.The obtained optical link observations are used as extensions for the perturbed network tomography model to ensure that the synthetic model can meetcompressive sensing constraints.Finally,the traffic matrix is estimated from the synthetic model by means of a compressive sensing recovery algorithm. A traffic matrix is a necessary parameter fornetwork management functions,and itsupplies a flow-level view of a largescale IP-over-WDM backbone network.This paper studies the problem of traffic matrix estimationand proposes an exact traffic matrix estimation approach based on network tomography techniques.The traditional network tomography model is extended to make it compatible with compressive sensing constraints.First,a stochastic perturbation is introduced in the traditional network tomography inference model.Then,an algorithm is proposed to achieve additional optical link observations via optical bypass techniques.The obtained optical link observations are used as extensions for the perturbed network tomography model to ensure that the synthetic model can meetcompressive sensing constraints.Finally,the traffic matrix is estimated from the synthetic model by means of a compressive sensing recovery algorithm.
出处 《China Communications》 SCIE CSCD 2016年第7期7-15,共9页 中国通信(英文版)
基金 supported in part by the National Natural Science Foundation of China(Nos.61571104,61071124,61501105) the General Project of Scientific Research of the Education Department of Liaoning Province(No.L20150174) the Program for New Century Excellent Talents in University(No.NCET-11-0075) the Fundamental Research Funds for the Central Universities(Nos.N150402003,N120804004,N130504003,N150404018) the State Scholarship Fund(201208210013)
关键词 traffic characterization traffic analysis compressive sensing WDM网络 流量矩阵 估计问题 旁路技术 over 层析成像技术 成像模型 光学
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参考文献13

  • 1K. Xu, M. Shen, Y. Cui, M. Ye, Y. Zhong, "A model approach to the estimation of peer-to-peer traffic matrices",lEEE Transactions on parallel and distributed systems, vol. 25, no. 5, pp. 1101 - 1111, 2014.
  • 2M. Polverini, A. lacovazzi, A. Cianfrani, et aL"Traffic Matrix Estimation Enhanced by SDNs Nodes in Real Network Topology", Proceedings of 2015 IEEE Conference on Computer Commu- nications Workshops, pp. 300-305, 2015.
  • 3D Kumlu, I. Hokelek, "Network Traffic Estimation using Markov Chain and Incremental Gaussian Mixture", Proceedings of 2015 23th Signal Pro- cessing and Communications Applications Con- ference, pp. 1187-1190, 2015.
  • 4M. Malboubi, C. Vu, C. Chuah, R Sharma, "De- centralizing network inference problems with multiple-description fusion estimation (MD- FE)",Proceedings of IEEE INFOCOM, pp. 1699- 1707, 2013.
  • 5A. Soule, A. Lakhina, N. Taft, K. Papagiannaki, K. Salamatian, A. Nucci, M. Crovella, C. Diot, "Traffic matrices: balancing measurements, inference and modeling", Proceedings of SIGMETRICS2005, pp. 362-373, 2005.
  • 6M, Roughan, Y. Zhang, W. Willinger, L. Qiu, "Spatio-temporar compressive sensing and In- ternet traffic matrices (extended version)", IEEE Transactions on Networking, vol. 20, no. 3, pp. 662-676, 2012.
  • 7L. Nie, D. Jiang, L. Guo, "A compressive sens- ing-based approach to end-to-end network traffic reconstruction utilizing partial measured origin-destination flows", Transactions on Emerging Telecommunications Technologies, vol. 26, no. 8, pp. 1108-1117, 2015.
  • 8L. Nie, D. Jiang, "A compressive sensing-based network tomography approach to estimating origin-destination flow traffic in large-scale backbone networks",lnternational Journal of Communication Systems, vol. 28, no. 5, pp. 889- 900, 2015.
  • 9Y. Zhang, M. Roughan, N. Duffield, et aL"Fast Accurate Computation of Large-scale IP Traffic Matrices from Link Loads", ACMSIGMETRICS Performance Evaluation Review, vol. 31, no. 2003, pp. 206-217, 2003.
  • 10D. Donoho, "Compressive sensing," IEEE Trans- actions on Information Theory, voi.52, no.4, pp. 1289-1306, 2006.

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