CALL FOR PAPERS https://www.comsoc.org/publications/magazines/ieee-network/cfp/big-data-intelligent-networking A vast amount of big data is opening the era of the data-driven solutions which will shape communication networks. Current networks are often designed based on the static end-to-end design principle, and their complexity has dramatically increased over the past several decades, which hinders the efficient and intelligent provision of big data. Both networking for big data and big data analytics in networking applications pose great challenges for industry and academic researchers. Small devices are continuously generating data, which are processed, cached, analyzed, and finally stored on in-network storages (e.g., routers), edge servers, or Clouds. From them, users efficiently and securely discover and fetch big data for diverse purposes. Intelligent networking technologies should be designed to effectively support such big data distribution, processing, and sharing. On the other hand, critical applications, such as industrial Internet of Things, connected vehicles, network monitoring/security/management, require fast mechanisms for real-time analysis of a huge number of events, as well as off-line analysis of massive historical data. These applications show strong demands to enable the networking decisions (e.g. routing, caching, security, and slicing) to be intelligent and automatic. Furthermore, big data analytic techniques to extract features and analyze the vast amount of data lead to a heavy burden on the networking, and therefore smart and scalable approaches must be conceived to enable them to be practical. The aim of this special issue is to answer some of the questions related to intelligent networking for big data and big data analytics for networking. The potential topics include, but are not limited to: - Networking architecture for big data - Machine learning, data mining and big data analytics in networking - Information-centric networking for big data - Software-defined network and network function virtualization for big data - Edge, fog, and mobile edge computing for big data - Security, trust, and privacy for big data networking - 5G and future mobile networks for big data sharing - Blockchain with big data networking - Data-center network for big data processing - Data analytics for networking big data - Distributed monitoring architectures for networking big data - Machine learning for network anomaly detection and security - 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 - Big data analytics for intelligent routing and caching - Big data networking in healthcare, smart cities, industry and other applications Submission Guidelines: Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Paper Submission Guidelines. All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the “July 2020: Big Data Intelligent Networking” topic from the drop-down menu of Topic/Series titles. Important Dates: Manuscript Submissions Deadline: 1 July 2019 Initial Decision Notification: 1 November 2019 Final Decision Notification: 1 March 2020 Final Manuscript Deadline: 1 April 2020 Publication Date: July 2020 Guest Editors: Ruidong Li, NICT, Japan Houbing Song, Embry-Riddle Aeronautical University, USA Jiannong Cao, Hong Kong Polytechnic University, Hong Kong Payam Barnaghi, University of Surrey, UK Jie Li, Shanghai Jiaotong University, China Constandinos X. Mavromoustakis, University of Nicosia, Cyprus --------------------------------------------------------------- For news of CHI books, courses & software, join CHI-RESOURCES mailto: [log in to unmask] To unsubscribe from CHI-ANNOUNCEMENTS send an email to mailto:[log in to unmask] For further details of CHI lists see http://listserv.acm.org ---------------------------------------------------------------