[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Cloud Computing Magazine Special Issue on "Cloud-based Smart Evacuation Systems for Emergency Management" IMPORTANT DATES ***************************** Submissions Due: August 20, 2014 DETAILS ABOUT THE ISSUE ***************************** 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 ***************************** 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 ***************************** Dr. Rajiv Ranjan, CSIRO, Australia raj.ranjan@csiro.au Dr. Samee Khan, NDSU, USA samee.khan@ndsu.edu Prof. Joanna Kolodziej, CUT, Poland joanna.kolodziej68@gmail.com Prof. Albert Zomaya, Sydney University, Australia zomaya@it.usyd.edu.au