An LSTM Framework for Software-Defined Measurement
暂无分享,去创建一个
[1] Dingde Jiang,et al. An Energy-Efficient Networking Approach in Cloud Services for IIoT Networks , 2020, IEEE Journal on Selected Areas in Communications.
[2] Zhihan Lv,et al. Big Data Analysis Based Network Behavior Insight of Cellular Networks for Industry 4.0 Applications , 2020, IEEE Transactions on Industrial Informatics.
[3] Houbing Song,et al. Rethinking Behaviors and Activities of Base Stations in Mobile Cellular Networks Based on Big Data Analysis , 2020, IEEE Transactions on Network Science and Engineering.
[4] Lei Shi,et al. A Compressive Sensing-Based Approach to End-to-End Network Traffic Reconstruction , 2020, IEEE Transactions on Network Science and Engineering.
[5] Laxmi N. Bhuyan,et al. DREAM: DistRibuted Energy-Aware traffic Management for Data Center Networks , 2019, e-Energy.
[6] Viktor K. Prasanna,et al. An LSTM Framework For Modeling Network Traffic , 2019, 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).
[7] Tarun Soni,et al. Network Traffic Prediction Using Recurrent Neural Networks , 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).
[8] Peng Liu,et al. Elastic sketch: adaptive and fast network-wide measurements , 2018, SIGCOMM.
[9] Diana Andreea Popescu,et al. Seek and Push: Detecting Large Traffic Aggregates in the Dataplane , 2018, ArXiv.
[10] Viktor K. Prasanna,et al. DeepFlow: a deep learning framework for software-defined measurement , 2017, CAN@CoNEXT.
[11] Xin Jin,et al. SketchVisor: Robust Network Measurement for Software Packet Processing , 2017, SIGCOMM.
[12] Guy Pujolle,et al. A Long Short-Term Memory Recurrent Neural Network Framework for Network Traffic Matrix Prediction , 2017, ArXiv.
[13] Jean C. Walrand,et al. Knowledge-Defined Networking , 2016, Comput. Commun. Rev..
[14] Vladimir Braverman,et al. One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon , 2016, SIGCOMM.
[15] Chen-Nee Chuah,et al. OpenMeasure: Adaptive flow measurement & inference with online learning in SDN , 2016, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[16] Minlan Yu,et al. FlowRadar: A Better NetFlow for Data Centers , 2016, NSDI.
[17] Yonggang Wen,et al. Data Center Energy Consumption Modeling: A Survey , 2016, IEEE Communications Surveys & Tutorials.
[18] Liansheng Tan,et al. Traffic matrix estimation: A neural network approach with extended input and expectation maximization iteration , 2016, J. Netw. Comput. Appl..
[19] Ramesh Govindan,et al. SCREAM: sketch resource allocation for software-defined measurement , 2015, CoNEXT.
[20] Sheng Wang,et al. Towards accurate online traffic matrix estimation in software-defined networks , 2015, SOSR.
[21] Abdulsalam Yassine,et al. Software defined network traffic measurement: Current trends and challenges , 2015, IEEE Instrumentation & Measurement Magazine.
[22] Amin Vahdat,et al. DREAM: dynamic resource allocation for software-defined measurement , 2015, SIGCOMM.
[23] Xin Huang,et al. Tango: Simplifying SDN Control with Automatic Switch Property Inference, Abstraction, and Optimization , 2014, CoNEXT.
[24] Chen-Nee Chuah,et al. Intelligent SDN based traffic (de)Aggregation and Measurement Paradigm (iSTAMP) , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.
[25] Paul Goransson,et al. Software Defined Networks: A Comprehensive Approach , 2014 .
[26] Fernando M. V. Ramos,et al. Software-Defined Networking: A Comprehensive Survey , 2014, Proceedings of the IEEE.
[27] Fernando A. Kuipers,et al. OpenNetMon: Network monitoring in OpenFlow Software-Defined Networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).
[28] Xin Li,et al. Distributed and collaborative traffic monitoring in software defined networks , 2014, HotSDN.
[29] Xin Huang,et al. Jive: Performance Driven Abstraction and Optimication for SDN , 2014, ONS.
[30] Ying Zhang,et al. An adaptive flow counting method for anomaly detection in SDN , 2013, CoNEXT.
[31] Min Zhu,et al. B4: experience with a globally-deployed software defined wan , 2013, SIGCOMM.
[32] Minlan Yu,et al. Software Defined Traffic Measurement with OpenSketch , 2013, NSDI.
[33] Matthew Roughan,et al. Internet Traffic Matrices: A Primer , 2013 .
[34] Marco Mellia,et al. Minimizing ISP Network Energy Cost: Formulation and Solutions , 2012, IEEE/ACM Transactions on Networking.
[35] Ming Zhang,et al. MicroTE: fine grained traffic engineering for data centers , 2011, CoNEXT '11.
[36] Sujata Banerjee,et al. DevoFlow: scaling flow management for high-performance networks , 2011, SIGCOMM.
[37] Nick McKeown,et al. A network in a laptop: rapid prototyping for software-defined networks , 2010, Hotnets-IX.
[38] Martin Suchara,et al. Greening backbone networks: reducing energy consumption by shutting off cables in bundled links , 2010, Green Networking '10.
[39] Sujata Banerjee,et al. ElasticTree: Saving Energy in Data Center Networks , 2010, NSDI.
[40] Monia Ghobadi,et al. OpenTM: Traffic Matrix Estimator for OpenFlow Networks , 2010, PAM.
[41] Dingde Jiang,et al. Large-Scale IP Traffic Matrix Estimation Based on the Recurrent Multilayer Perceptron Network , 2008, 2008 IEEE International Conference on Communications.
[42] Kavé Salamatian,et al. Combining filtering and statistical methods for anomaly detection , 2005, IMC '05.
[43] Rui Xu,et al. Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.
[44] Thomas Magedanz,et al. From networks and network management into service and service management , 1996, Journal of Network and Systems Management.
[45] Mikkel Thorup,et al. Traffic engineering with estimated traffic matrices , 2003, IMC '03.
[46] Philippe Owezarski,et al. Modeling Internet backbone traffic at the flow level , 2003, IEEE Trans. Signal Process..
[47] Konstantina Papagiannaki,et al. Long-term forecasting of Internet backbone traffic: observations and initial models , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).
[48] George Varghese,et al. New directions in traffic measurement and accounting , 2002, CCRV.
[49] San-qi Li,et al. A predictability analysis of network traffic , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).
[50] Kavitha Chandra,et al. Time series models for Internet data traffic , 1999, Proceedings 24th Conference on Local Computer Networks. LCN'99.
[51] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.