An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcemen...
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning
About this item
Full title
Author / Creator
Zhu, Lin , Tan, Long , Li, Bingxian and Tian, Huizi
Publisher
John Wiley & Sons, Inc
Journal title
Language
English
Formats
Publication information
Publisher
John Wiley & Sons, Inc
Subjects
More information
Scope and Contents
Contents
Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real‐time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this article proposes a vehicul...
Alternative Titles
Full title
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_f654c66d10c94a70b66ba560e312d7a2
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f654c66d10c94a70b66ba560e312d7a2
Other Identifiers
ISSN
1751-8628
E-ISSN
1751-8636
DOI
10.1049/cmu2.12800
