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NETWORK MEASUREMENT

Network Measurement: Inventory
DISCO.png

FLOW STATISTICS

We have successfully established a complete theoretical foundation called adaptive nonlinear sampling theory for efficient network measurement. The sampling function family, which is the key of the proposed theory, is demonstrated to be the optimal form later by other researchers. This work nicely solves the previous difficulties to accurately estimate the flow attributes with commodity hardware at line rate. In addition, we further develop the theory for expansion into the SDN scenario.

  1. Chengchen Hu, Bin Liu, Hongbo Zhao, Kai Chen, Yan Chen, Yu Cheng, Hao Wu, Discount Counting for Fast Flow Statistics on Flow Size and Flow Volume, IEEE/ACM Transactions on Networking, vol.22(3): 970 – 981, 2014.

  2. Chengchen Hu, Sheng Wang, Jia Tian, Bin Liu, Yan Chen, Yu Cheng, ANLS: Adaptive Non-Linear Sampling Method for Accurate Flow Size Measurement, IEEE transactions on Communications, Vol. 60, No. 3, pp. 789 – 798. 2012.

  3. Chengchen Hu, Bin Liu, Hongbo Zhao, Kai Chen, Yan Chen, Chunming Wu and Yu Cheng, “DISCO: Memory Efficient and Accurate Flow Statistics for Network Measurement“, Proceeding of IEEE ICDCS 2010, Genoa, Italy, June 21-25, 2010.

  4. Chengchen Hu, Sheng Wang, Jia Tian, Bin Liu, Yan Chen, Yu Cheng,  “Accurate and Efficient Traffic Monitoring Using Adaptive Non-linear Sampling Method“, Proceeding of IEEE INFOCOM 2008, Phoenix, USA, 2008.

  5. Ji Yang, Chengchen Hu, Peng Zheng, Ruilong Wang, Peng Zhang, and Xiaohong Guan. 2016. Rethinking the Design of OpenFlow Switch Counters. In Proceedings of the 2016 conference on ACM SIGCOMM 2016 Conference (Poster at ACM SIGCOMM ’16).

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NETWORK MEASUREMENT BASED MANAGEMENT

We have learnt from measurement results, which helped us to address network research problems and further guided us to solve the problems. The “measure- first-design-later” philosophy was applied to quite wide scenarios including inter-domain routing recovery, WSN configuration, queue scheduling, P2P networks, etc.

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  1. Songwei Fu, Yan Zhang, Yuming Jiang, Chengchen Hu, Chia-Yen Shih, and Pedro Jose Marron, Experiment study for multi-layer parameter configuration of WSN links, 35th IEEE International Conference on Distributed Computing Systems (ICDCS 2015), Columbus, Ohio, USA on June 29 – July 2, 2015.

  2. Chengchen Hu, Danfeng Shan, Yu Cheng, Tao Qin,Inter-Swarm Content Distribution Among Private BitTorrent Networks, IEEE Journal on Selected Areas in Communications, vol. 31(9): 132 – 141, 2013

  3. Chengchen Hu, Kai Chen, Y an Chen, Bin Liu, Athanasios V . V asilakos, A Measurement Study on Potential Inter-Domain Routing Diversity, IEEE Transactions on Network and Service Management, Vol. 9, No. 3, pp. 268 – 278, 2012

  4. Chengchen Hu, Kai Chen, Yan Chen and Bin Liu, “Evaluating Potential Routing Diversity for Internet Failure Recovery“, Proceeding of IEEE INFOCOM 2010, San Diego, CA, USA, March 15-19, 2010.

  5. Chengchen Hu, Yi Tang, Xuefei Chen, Bin Liu, “Per-flow Queueing by Dynamic Queue Sharing“, Proceeding of IEEE INFOCOM 2007, Anchorage, Alaska, USA, 2007.

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BIG NETWORK DATA

Analysis on big network data is challenging since one has to handle a massive and rapidly increasing amount of data from many different sources at line rate. Our work addressing the problem are mainly in two categories: one is to inspect the compressed streaming traffic directly, the other is a processing model called Deep semantics inspection (DSI). The key idea of DSI is to obtain a sketch of user behavior at wire speed and then semantics analysis is applied to the obtained sketch with a size several orders of magnitude smaller than that of raw data.

  1. Chengchen Hu, Hao Li, Yuming Jiang, Yu Cheng and Paul Heegaard, “Deep semantics inspection over big network data at wire speed,” in IEEE Network, vol. 30, no. 1, pp. 18-23, January-February 2016.

  2. Hao Li, Chengchen Hu, MP-ROOM: Optimal Matching On Multiple PDUs for Fine-Grained Traffic Identification, IEEE Journal on Selected Areas in Communications,Vol. 32 (10): 1881 – 1893, 2014.

  3. Hao Li, Chengchen Hu, ROOM: Rule Organized Optimal Matching for Fine-Grained Traffic Identification,IEEE INFOCOM 2013 mini-conference, Turin, Italy, April 14-19, 2013

  4. Xiuwen Sun, Hao Li, Xingxing Lu, Dan Zhao, Zheng Peng, Chengchen Hu, Towards a Fast Regular Expression Matching Method over Compressed Traffic, Proceedings of IWQoS’18

  5. Xiuwen Sun, Kaiyu Hou, Hao Li, Chengchen Hu, Towards A Fast Packet Inspection over Compressed HTTP Traffic, in the proceeding of IEEE IWQoS 2017, VILANOVA I LA GELTRÚ, SPAIN 14-16 JUNE 2017.

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