Vision and Challenges for Knowledge Centric Networking

Dapeng Wu, Zhenjiang Li, Jianping Wang, Yuanqing Zheng, Mo Li, Qiuyuan Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Article number8685777
Pages (from-to)117-123
Number of pages7
JournalIEEE Wireless Communications
Volume26
Issue number4
DOIs
Publication statusPublished - Aug 2019

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this