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Scope
Big Data Networks welcomes submissions concerning all aspects of Big Data that touch on communication networks, which can include both data networking, networking design, management and measurement, and also higher layer application networks. The key property of submissions is that they must be motivated by issues of scale in these contexts.
Scope
The relentless increase of scale and complexity of communications networks and the data they carry presents enormous challenges for their design and operation. The proliferation of network endpoints brought about by the Internet of Things, and the ability to virtualize many network and host functions are major drivers in this scaling. Furthermore, billions of users employ services and applications mediated by these networks, generating huge numbers of daily interactions.
Big Data Networks welcomes submissions concerning all aspects of Big Data that touch on communication networks, which can include both data networking, networking design, management and measurement, and also higher layer application networks. The key property of submissions is that they must be motivated by issues of scale in these contexts.
Submissions to Big Data Networks are no longer possible via Frontiers in Digital Humanities, as this field journal is now closed. This section still welcomes submissions via Frontiers in Big Data or Frontiers in ICT.
Indexed in: Scopus, Google Scholar, DOAJ, CrossRef, dblp, Ulrich's Periodicals Directory, CLOCKSS
PMCID: NA
Big Data Networks welcomes submissions of the following article types: Book Review, Brief Research Report, Code, Correction, Data Report, Editorial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Policy and Practice Reviews, Review, Specialty Grand Challenge and Technology Report.
All manuscripts must be submitted directly to the section Big Data Networks, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
Articles published in the section Big Data Networks will benefit from the Frontiers impact and tiering system after online publication. Authors of published original research with the highest impact, as judged democratically by the readers, will be invited by the Chief Editor to write a Frontiers Focused Review - a tier-climbing article. This is referred to as "democratic tiering". The author selection is based on article impact analytics of original research published in all Frontiers specialty journals and sections. Focused Reviews are centered on the original discovery, place it into a broader context, and aim to address the wider community across all of ICT and Big Data.
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