CHI-ANNOUNCEMENTS Archives

ACM SIGCHI General Interest Announcements (Mailing List)

CHI-ANNOUNCEMENTS@LISTSERV.ACM.ORG

Options: Use Forum View

Use Monospaced Font
Show Text Part by Default
Condense Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Content-Type:
text/plain; charset="UTF-8"
Date:
Tue, 26 Dec 2017 17:32:44 +1300
Reply-To:
confs xyz <[log in to unmask]>
Subject:
MIME-Version:
1.0
Message-ID:
Content-Transfer-Encoding:
quoted-printable
Sender:
"ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
From:
confs xyz <[log in to unmask]>
Parts/Attachments:
text/plain (161 lines)
*** OUR SINCERE APOLOGIES IF YOU RECEIVE MULTIPLE COPIES OF THIS
ANNOUNCEMENT
***
——————————————————————————————————————
========================================================================
CALL FOR PAPER

SCI indexed journal (IF: 1.898) Wireless Communications and Mobile
Computing Special Issue on "Big IoT Data Analytics in Fog Computing"
https://www.hindawi.com/journals/wcmc/si/716105/cfp/

========================================================================
The number of devices within Internet of Things (IoT) that are connected
and available via Internet will be between 50 and 100 billion by 2020. The
IoT devices are

typically the sensors embedded in environments, buildings, vehicles,
manufacturing processes, and products or attached to the people. The amount
of the data generated

by IoT devices grows exponentially as these devices operate nonstop, 24/7,
creating an avalanche of data that is out of the control of existing and
foreseeable data

processing and analytics techniques. On the other hand, we can create
numerous opportunities to extract unprecedented insightful information.
Unlocking the value of

big data through analytics and mining has been regarded as the key enabler
of many innovation and marketing strategies which, in turn, has pushed more
efforts and

supports to the IoT and big data related R&D. While data processing is
typically envisaged to be conducted in clouds, it alone is suffering from
growing limitations in

meeting demands of numerous applications where the local computation nearby
data sources is required for low-latency response, contextual information
integration, or

networking load reduction. Meanwhile, moving all the data generated from
IoT devices into cloud server farms for further processing or storage poses
overwhelming

challenges on the Internet infrastructure and is often prohibitively
expensive, technically impractical, and mostly unnecessary.

Fog computing is an emerging paradigm based on the creation of micro clouds
(called fog nodes) near the sources of data. It is a promising approach to
processing data

before they even attempt to reach cloud, shortening the communication times
and cost, as well as reducing the need for huge data storage. It seamlessly
bridges IoT

devices and the remote cloud data centers by pushing cloud computing,
storage, and networking services down closer to end IoT devices. Fog
computing has seen a rapidly

increasing number of applications in many industries such as manufacturing,
e-health, oil and gas, smart cities, smart homes, and smart grids. However,
it is still in

its early stages and presents a set of new challenges with the increasing
adoption of this computing paradigm, such as fog architecture, frameworks,
and standards,

computing, storage and networking resource provisioning and scheduling,
programming abstracts and models, and security and privacy issues. In
particular, big IoT data

analytics with fog computing infrastructure is in its nascent stage but of
paramount importance and requires extensive research in order to conduct
more efficient

knowledge discovery and smart decision support.

Many relevant theoretical and technical issues have not been answered well
yet, for example, how to abstract programming interfaces of fog
infrastructure and platforms

for data analytics, how to design scalable data mining algorithms with the
use of fog infrastructure, how to achieve secure and privacy-preserving
data analytics in

fog computing. As such, it is high time that the related issues in big IoT
data analytics with fog infrastructure will be investigated by examining
fog architecture,

platforms, and applications in detail, hence the call for this special
issue.

Potential topics include but are not limited to the following:

Fog architectures, frameworks, standards, and platforms for IoT data
analytics
Fog programming abstracts, models, and toolkits for data analytics
Wireless communication supports for fog computing
Mobile computing with the support of fog computing
Load balancing and resource scheduling and management in fog computing
Middleware for distributed data management in fog computing
Data mining and machine learning algorithm design in fog computing
Theory and modelling of distributed intelligence in fog computing for IoT
data analytics
Multisource and heterogeneous IoT data analytics with fog
Time-critical and low-latency data analytics with fog
Spatial and temporal data processing and analytics in fog computing
Fog data analytics applications, for example, smart cities, e-health, and
smart homes
Information retrieval design and knowledge assistance for fog computing
data analytics
Context-aware IoT applications in the fog
Disaster and emergency management in IoT with fog
Recovery schemes in case of fog down
Pricing models for IoT data analytics in fog computing
Privacy and security issues related to fog data analytics

========================================================================
Authors can submit their manuscripts through the Manuscript Tracking System
at https://mts.hindawi.com/submit/journals/wcmc/bdafc/.

Submission Deadline Friday, 26 January 2017
Publication Date June 2018
Papers are published upon acceptance, regardless of the Special Issue
publication date.

========================================================================
Wireless Communication and Mobile Computing (WCMC)
The most recent Impact Factor for Wireless Communications and Mobile
Computing is 1.899 according to the 2016 Journal Citation Reports released
by Clarivate Analytics

in 2017.

Presenting comprehensive coverage of this fast moving field, Wireless
Communications and Mobile Computing provides the R&D communities working in
academia and the

telecommunications and networking industries with a forum for sharing
research and ideas. Wireless Communications and Mobile Computing is
included in many leading

abstracting and indexing databases.

========================================================================
Guest Editors:
Xuyun Zhang, University of Auckland, Auckland, New Zealand
Yongrui Qin, University of Huddersfield, West Yorkshire, UK
Deepak Puthal, University of Technology Sydney, Ultimo, Australia
Xiaobing Wu, University of Canterbury, Christchurch, New Zealand

    ---------------------------------------------------------------
    For news of CHI books, courses & software, join CHI-RESOURCES
     mailto: [log in to unmask]

    To unsubscribe from CHI-ANNOUNCEMENTS send an email to
     mailto:[log in to unmask]

    For further details of CHI lists see http://listserv.acm.org
    ---------------------------------------------------------------

ATOM RSS1 RSS2