• Feb 07, 2023 News!JACN will adopt Article-by-Article Work Flow. The benefit of article-by-article workflow is that a delay with one article may not delay the entire issue. Once a paper steps into production, it will be published online soon.   [Click]
  • May 30, 2022 News!JACN Vol.10, No.1 has been published with online version.   [Click]
  • Dec 24, 2021 News!Volume 9 No 1 has been indexed by EI (inspec)!   [Click]
General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Shira Lu
    • Abstracting/ Indexing: INSPEC (IET), EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

Journal of Advances in Computer Networks (JACN) is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of computer networks. The focus is to publish papers on state-of-the-art computer networks. Submitted papers will be reviewed by technical committees of the journal and association. The audience includes researchers, managers and operators for computer networks as well as designers and developers.

All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing.
Featured Article
A Comparison between Text, Parquet, and PCAP Formats for Use in Distributed Network Flow Analysis on Hadoop
Miguel Zenon Nicanor L. Saavedra and William Emmanuel S. Yu
Hadoop's popularity as a distributed computing platform continues to grow as more and more data is generated each year. As a fault-tolerant and horizontally scalable ecosystem, it becomes a suitable platform for the analysis of big network data. While most network data are currently being analyzed by vertically scaled machines, Hadoop provides an alternative method of analysis...[Read More]
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E-mail: jacn@ejournal.net