Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105573
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | en_US |
dc.creator | Wu, D | en_US |
dc.creator | Li, Z | en_US |
dc.creator | Wang, J | en_US |
dc.creator | Zheng, Y | en_US |
dc.creator | Li, M | en_US |
dc.creator | Huang, Q | en_US |
dc.date.accessioned | 2024-04-15T07:35:07Z | - |
dc.date.available | 2024-04-15T07:35:07Z | - |
dc.identifier.issn | 1536-1284 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/105573 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.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. | en_US |
dc.rights | 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. | en_US |
dc.title | Vision and challenges for knowledge centric networking | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.description.otherinformation | Title on author’s file: Vision and Challenges for Knowledge Centric Networking (KCN) | en_US |
dc.identifier.spage | 117 | en_US |
dc.identifier.epage | 123 | en_US |
dc.identifier.volume | 26 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.doi | 10.1109/MWC.2019.1800323 | en_US |
dcterms.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. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE wireless communications, Aug. 2019, v. 26, no. 4, p. 117-123 | en_US |
dcterms.isPartOf | IEEE wireless communications | en_US |
dcterms.issued | 2019-08 | - |
dc.identifier.scopus | 2-s2.0-85064706882 | - |
dc.identifier.eissn | 1558-0687 | en_US |
dc.description.validate | 202402 bcch | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | COMP-0548 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 20981062 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Zheng_Vision_Challenges_Knowledge.pdf | Pre-Published version | 1.08 MB | Adobe PDF | View/Open |
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