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Welcome to IEEE Technical Committee on Big Data

IEEE SIG on Big Data Intelligent Networking

Chair: Ruidong Li, National Institute of Information and Communications Technology (NICT), Japan, Email: lrd@nict.go.jp
Vice-Chair: Houbing Song, Embry-Riddle Aeronautical University, USA, Email: houbing.song@erau.edu
Vice-Chair: Xiaoming Fu, Gottingen University, Germany, Email: fu@cs.uni-goettingen.de
Vice-Chair: Kui Wu, University of Victoria, Canada, Email: wkui@uvic.ca
Vice-Chair: Payam Barnaghi, University of Surrey, UK, Email: p.barnaghi@surrey.ac.uk
Vice-Chair: Zhou Su, Shanghai University, China, Email: zhousu@ieee.org
Vice-Chair: Constandinos Mavromoustakis, University of Nicosia, Cyprus, Email: mavromoustakis.c@unic.ac.cy
Advisor: Jiannong Cao, Hong Kong Polytechnic University, Hongkong, Email: csjcao@comp.polyu.edu.hk
Advisor: Hsiao-Hwa Chen, National Cheng Kung University, Taiwan, Email: hshwchen@mail.ncku.edu.tw
Advisor: Wenjing Lou, Virginia Tech, USA, Email: wjlou@vt.edu
Advisor: Chonggang Wang, Interdigital, USA, Email: cgwang@ieee.org
Advisor: Jie Wu, Temple University, USA, Email: jiewu@temple.edu
Advisor: Hitoshi Asaeda, National Institute of Information and Communications Technology (NICT), Japan, Email: asaeda@nict.go.jp

Scope and Objectives

Big data are transforming the world and open the era of the new paradigm for science discovery through data-driven approach. This paradigm also brings out great influences on networking research area. The current networks are designed based on the static end-to-end design principle, and their complexity has dramatically increased in the past several decades, which hinders the efficient and intelligent provision of big data services and makes it important and challenging to design network applications based on big data and in-network computation. That is, both networking for big data (e.g., collection, computation, analysis, and visualization) and big data analytics and in-network computation for networking applications (e.g. monitoring, routing, caching, and security) show great challenges for industries and academia.

Regarding networking for big data, the big data mining and learning applications depend on the efficient and effective support from the underneath networking protocols. Big data are collected from small devices, processed/cached/analyzed in the network, and finally stored at the servers or clouds. The big data applications involve the data sources from different geographically distributed data centers or in-network storages. Huge amount of users efficiently and securely search, discover and fetch the big data from the data centers or in-network storages. Regarding big data analytics for networking, critical applications such as network monitoring, network security or dynamic network management require fast mechanisms for on-line analysis of thousands of events per second, as well as efficient techniques for off-line analysis of massive historical data. The applications making networking decisions (e.g. routing, caching, and security) from the ever-growing amount of measurement data is becoming a big challenge, which remains poorly understood and investigated. Furthermore, big data analytic techniques to characterize, detect, locate and analyze complex behaviors bring out much burden for networking, and thus the smart and scalable approaches must be conceived to enable them to be practical. The analysis on the network status data shows the great potential to improve the performance of networking and applications.

In summary, this SIG will focus on the technical challenges and applications of intelligent networking for and by big data and in-network computation. We envision that the combination of big data with networking will provide more efficient support for big data applications and enable more intelligent networking applications. The areas of interests include, but are not limited to, the following:

• Networking architecture for big data
• Big data with in-network computation
• Networking big data analysis
• Machine learning, data mining and big data analytics in networking
• Deep learning for networking
• Information-centric networking for big data
• Software-defined network for big data
• Networking for distributed machine learning
• Queueing theory analysis for big data applications
• Edge, fog, and mobile edge computing for big data
• Privacy and trust management for big data networking
• Authentication, authorization, accountability for big data networking
• Sensor, drone, ad-hoc networks for big data collection and distribution
• 5G and future mobile networks for big data sharing
• Performance modeling in networking for big data
• Mobility and big data
• Network virtualization for big data
• Blockchain with big data networking
• Big data analytics for blockchain
• Big data for disaster-resilient networking
• Data-center network for big data processing
• Application of reinforced-learning for networking
• Data analytics for network measurement data mining
• Big data analysis frameworks for network monitoring data
• Distributed monitoring architectures for networking big data
• Networking-based benchmarks for big data analysis
• Machine learning for network anomaly detection and security
• Network anomaly diagnosis through networking big data
• In-network computation for intelligent networking
• Big data analytics for network management
• Distributed artificial intelligence for networking
• Efficient networking for distributed artificial intelligence
• Big data analytics and visualization for network traffic
• Research challenges on big data analytics for networking
• Big data analytics for intelligent routing and caching

Founding Members

  1. Ruidong Li, National Institute of Information and Communications Technology (NICT), Japan
  2. Houbing Song, Embry-Riddle Aeronautical University, USA,
  3. Constandinos Mavromoustakis, University of Nicosia, Cyprus
  4. Zhou Su, Shanghai University, China
  5. Kui Wu, University of Victoria, Canada
  6. Burak Kantarci, University of Ottawa, Canada
  7. Jie Wu, Temple University, USA
  8. Hsiao-Hwa Chen, National Cheng Kung University, Taiwan
  9. Xiaoming Fu, Gottingen University, Germany
  10. Rongxing Lu, University of New Brunswick, Canada
  11. Guido Dartmann, University of Applied Sciences Trier, Germany
  12. Jie Li, Shanghai Jiao Tong University, China
  13. Anke Schmeink, RWTH Aachen University, Germany
  14. Mohammad Shojafar, University of Padua, Italy
  15. Jinsong Wu, University of Chile, Chile
  16. Hai Jin, Huazhong University of Science and Technology, China
  17. Payam Barnaghi, University of Surrey, UK,
  18. Jiannong Cao, Hong Kong Polytechnic University, Hongkong
  19. Wei Bao, University of Sydney, Australia
  20. Xiaojiang Du, Temple University, USA
  21. Panlong Yang, University of Science and Technology of China, China
  22. Lin Cai, University of Victoria, Canada
  23. Guang Cheng, Southeast University, China
  24. Chen Qian, University of California Santa Cruz, USA
  25. Jun Bi, Tsinghua University, China
  26. Chonggang Wang, Interdigital, USA
  27. Liming Sun, Chinese Academy of Sciences, China
  28. Alex Liu, Michigan State University, USA
  29. Hitoshi Asaeda, National Institute of Information and Communications Technology (NICT), Japan
  30. Qitao Gan, Telenor, Norway
  31. Kai Lei, Peking University, China
  32. Wenjing Lou, Virginia Tech, USA
  33. Bin Xiao, Hong Kong Polytechnic University, Hongkong
  34. Dongming Peng, University of Nebraska-Lincoln, USA
  35. Kristian Skracic, Ericsson Nikola Tesla d.d., Croatia
  36. Yingfei Dong, University of Hawaii, USA
  37. Hongjian Sun, Durham University, U.K.
  38. Yu Jiang, Tsinghua University, China
  39. Jian Tang, Syracuse University, USA
  40. Dan Wang, Hong Kong Polytechnic University, Hongkong
  41. Minho Jo, Korea University, Korea
  42. Yong Cui, Tsinghua University, China
  43. Takuji Tachibana, University of Fukui, Japan
  44. Mo Sha, State University of New York at Binghamton, USA
  45. Hui Zang, Huawei Research, USA
  46. Feng Ye, University of Dayton, USA
  47. Elias Bou-Harb, Florida Atlantic University, USA
  48. Jongwon Kim, Gwangju Institute of Science and Technology, Korea
  49. Humphrey Rutagemwa, Communications Research Centre, Canada
  50. Yuki Koizumi, Osaka University, Japan
  51. Dingde Jiang, University of Electronic Science and Technology of China, China
  52. Miao Pan, University of Houston, USA
  53. Ali M. Al-Salim, University of Leeds, U. K.
  54. Yunfei Ma, Massachusetts Institute of Technology, USA

Linkedin HP:

https://www.linkedin.com/groups/8673834

Google sites:

https://sites.google.com/site/tcbdinieee/

---------------------------Activities-----------------------------------------------

ICDCS 2019 workshop on Network Meets Intelligent Computations (NMIC)

https://www.eee.hku.hk/~kcleung/service/NMIC/2019/cfp.html

IEEE Network Magazine SI on Big Data Intelligent Networking:

https://www.comsoc.org/publications/magazines/ieee-network/cfp/big-data-intelligent-networking

Transactions on Emerging Telecommunications Technologies (ETT)

Special Issue on Intelligent Resource Management in Cloud Computing and Networking:

https://wol-prod-cdn.literatumonline.com/pb-assets/assets/21613915/Intelligent%20Resource%20Management%20in%20Cloud%20Computing%20and%20Networking.pdf

IEEE INFOCOM 2019 Intelligent Cloud Computing and Networking (ICCN) workshop:

https://infocom2019.ieee-infocom.org/workshop-intelligent-cloud-computing-and-networking

IEEE ICC 2019 FIRST INTERNATIONAL WORKSHOP ON DATA DRIVEN INTELLIGENCE FOR NETWORKS AND SYSTEMS (DDINS):

https://icc2019.ieee-icc.org/workshop/w15-first-international-workshop-data-driven-intelligence-networks-and-systems-ddins

------------------------Other Related SDO Activities-----------------------------------

IETF/IRTF Computing in the Network (COIN):

https://trac.ietf.org/trac/irtf/wiki/coin

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