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Title: Vision and challenges for knowledge centric networking
Authors: Wu, D
Li, Z
Wang, J
Zheng, Y 
Li, M
Huang, Q
Issue Date: Aug-2019
Source: IEEE wireless communications, Aug. 2019, v. 26, no. 4, p. 117-123
Abstract: In the creation of a smart future information society, IoT and CCN break two key barriers for both front-end sensing and back-end networking. However, we still observe the missing piece of the research that dominates current networking traffic control and system management, for example, lacking the knowledge penetrated into both sensing and networking to glue them holistically. In this article, we propose leveraging emerging machine learning or deep learning techniques to create aspects of knowledge to facilitate the designs. In particular, we can extract knowledge from collected data to facilitate reduced data volume, enhanced system intelligence and interactivity, improved service quality, communication with better controllability and lower cost. We this knowledge-oriented traffic control and networking management paradigm Knowledge Centric Networking (KCN). This article presents the rationale for KCN, its benefits, related works and research opportunities.
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE wireless communications 
ISSN: 1536-1284
EISSN: 1558-0687
DOI: 10.1109/MWC.2019.1800323
Rights: ©2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication D. Wu, Z. Li, J. Wang, Y. Zheng, M. Li and Q. Huang, "Vision and Challenges for Knowledge Centric Networking," in IEEE Wireless Communications, vol. 26, no. 4, pp. 117-123, August 2019 is available at https://doi.org/10.1109/MWC.2019.1800323.
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