[hpc-announce] CFP: IEEE Cloud Computing Magazine SI on "Cloud-based Smart Evacuation Systems for Emergency Management"

[DEEPAK PUTHAL]

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 *Call for papers:*

IEEE Cloud Computing Magazine

Special Issue on "Cloud-based Smart Evacuation Systems for Emergency
Management"


IMPORTANT DATES

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Submissions Due: August 20, 2014


DETAILS ABOUT THE ISSUE

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Natural and man-made emergencies, such as tsunamis, earthquakes, floods,
and epidemics pose a significant threat to human societies. The lessons
learned from the growing number of recent emergencies, such as Japan's
earthquake (2011), Katrina hurricane (2005), Colorado flood (2013),
Queensland flooding in Australia (2010), Haiti earthquake (2010), has put
impetus on the development of emergency evacuation planning systems.
Well-coordinated emergency management activities that involves guiding of
citizens out of danger areas, placement of medical team to the most
appropriate locations, and real-time planning of evacuation routes before
and after a disaster play a significant role in saving lives, protecting
critical infrastructures, and minimizing causalities. For example, due to
lack of proper evacuation planning system, 25 people lost their lives in
the first 30 minutes while attempting to flee their Oakland Hills
neighborhood in California during a wildfire in 1991.

The management of evacuation activities such as guiding people out of
dangerous areas and coordinating rescue teams is dependent on the
availability of historical data as well as on the effective real-time
integration and utilisation of data streaming from multiple sources
including on-site sensors, social media feeds and messaging on mobile
devices (i.e. text messaging, location, etc.). However, there is a pitfall;
the growing ubiquity of on-site sensors, social media and mobile devices
means there are more sources of outbound traffic, which ultimately results
in the creation of a tsunami of data, beginning shortly after the onset of
emergency events. This data tsunami phenomenon is being described as a new
grand challenge in computing: The 'Big Data' problem. Over 20 million
tweets posted during Hurricane Sandy (2012) lead to an instance of the Big
Data problem. During the 2010 Haiti earthquake, text messaging via mobile
phones and Twitter made headlines as being crucial for disaster response,
but only some 100,000 messages were actually processed by government
agencies due to lack of automated and scalable data processing
infrastructure.

Design and development of evacuation systems for emergency management
requires a complete ICT (Information and Communication Technology) paradigm
shift in a way that systems do not get overwhelmed by incoming data volume,
data rate, data sources, and data types. New cloud-based techniques are
needed that can extract meaningful information from large-scaled data in
real-time, while avoiding unnecessary data transmission or storage. Future
initiative should focus on developing cloud-based techniques to improve the
performance of multiple data stream processing system while balancing
computational complexity and Quality of Service (e.g., decision making
delay, alert generation delay, etc.).

*We solicit papers and columns from both industrial and academic research
communities.*


SUBMISSION GUIDELINES

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Submissions will be subject to the IEEE Cloud Computing Magazines'
peer-review process. Articles should be at most 6,000 words, with a maximum
of 15 references, and should be understandable to a broad audience of
people interested in cloud computing, big data and related application
areas. ¬ The writing style should be down to earth, practical, and
original. Authors should not assume that the audience will have specialized
experience in a particular sub field. All accepted articles will be edited
according to the IEEE Computer Society style guide. Submit your papers to
Manuscript Central at https://mc.manuscriptcentral.com/cs-cc.


If any questions please contact the guest editors.



GUEST EDITORS

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Dr. Rajiv Ranjan, CSIRO, Australia
raj.ranjan at csiro.au

Dr. Samee Khan, NDSU, USA
samee.khan at ndsu.edu

Prof. Joanna Kolodziej, CUT, Poland
joanna.kolodziej68 at gmail.com

Prof. Albert Zomaya, Sydney University, Australia
zomaya at it.usyd.edu.au
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