• Jul 04, 2018 News!JACN Vol.6, No.1 has been published with online version.   [Click]
  • Jun 05, 2018 News!ICINT 2018 (The annual meeting of JACN) has been successfully held in Osaka, Japan during May 24-26.   [Click]
  • May 22, 2018 News!JACN has been included in EBSCO database.
General Information
    • ISSN: 1793-8244
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET),  Electronic Journals Library, Ulrich's Periodicals Directory, EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Dr. Ka Wai Gary Wong
Division of Information and Technology Studies, Faculty of Education, The University of Hong Kong.
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
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All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed.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