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Elsevier Ad Hoc Networks Special Issue on
Big Data Inspired Data Sensing, Processing and Networking Technologies


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Big data is the current big thing in computing after cloud computing and it is in par with  software  defined  network  (SDN)  in  communications  and  networks field.  It  is evident  that  big  data  is  making  big  impact  to  diverse  walks  of  our  everyday  life, ranging  from  increasing  understanding  of  digital  system  or human/social behaviours/processes  to  promoting  economic  growth  and  eventually  to  improving human  being’s  health  and  quality  of  life.  A  long-term strategy  to  address  various challenges  introduced  or  inspired  by  big  data  shall  be  a  systematic  one  that  brings together  the  three  key  aspects  of  a  big data  system,  namely,  data  sensing,  data processing and data communications.

This  Special  Issue  expects  to  address  big  data  issues  related  to  data  sensing,  data processing  and  data  communications,  including  high-level ideology/methodology, concrete big data inspired data sensing/processing/networking technologies, big data system architecture, QoS, energy-efficiency, and fault tolerance in big data systems, management of big data systems, service engineering and algorithm design, and real world deployment experiences. Paper can address any individual component in a big data  system  or  an  integration  of  them.  It  is  at  the  author’s  disposal  as  to  which particular technology to choose.

The  goal  of this SI is to highlight and systematically address the challenges arising from  big  data.  The  collection  of  the  articles  in  this  SI  will  create  a  forum for researches, developers and practitioners from both academia and industr y to publish the key results and to disseminate the state -of-the-art concepts and techniques in all aspects of big data. This SI will also serve as a stimulus to educate about, promote and accelerate technological evolution toward big data. Specifically, t he special issue will present original research articles that cover the following subjects (but are not limited to): 

  • Big  data  inspired  data  sensing  technologies,  modelling,  algorithms  and systems 
  • Big  data  inspired  data  processing  technologies,  modelling,  algorithms  and systems including image processing, computer vision
  • Big data inspired data communication and networking technologies, modelling, algorithms  including  optical/MPLS  core  networks,  IP  core  networks,  fixed broadband  access  network  technologies  such  as  passive  optical  networks (PONs),  mobile  wireless  broadband  access  technologies  (such  as  WiFi, WiMAX,  LTE,  LTE-A,  5G,  etc),  and  also  the  combination  and/or convergence of the above
  • Hybridization of the above three individual key aspects. e.g., convergence of data  sensing  with  data  pre-processing,  cross-layer  design  of  big  data processing together with stream data transmission, etc
  • Energy-efficient big data systems
  • Quality of Service assurance in big data systems
  • Fault tolerance in big data systems
  • Big data system management and adaptation
  • Application-layer service engineering for big data
  • Testing and evaluation tools
  • Prototype systems and real-world deployment experiences

Manuscript Submission
With regard to  both the content and formatting style  of  the submissions, prospective contributors should follow the Elsevier Ad Hoc Networks guidelines for authors that can be found at  http://www.elsevier.com/journals/ad-hoc-networks/1570-8705/guidefor-authors.  Authors should submit their manuscripts through the  online submission and editorial system  for Ad Hoc Networks Journal at  http://ees.elsevier.com/adhoc/. 
Choose  "Special  Issue  –  Big  Data Inspired  SPN" from the drop down menu on the submission page. 

Important Date
Manuscript Submission Due    30th November 2014
Acceptance Notification             31st Mar 2015
Final Manuscript Due                  30th April 2015
Publication                                     May-June 2015


Guest Editors 
Jia Hu                   Department  of  Mathematics  and  Computer  Science, Liverpool Hope University, Hope  Park, Liverpool,  L16 7PP, United Kingdom
                              Tel: +44 151 2913978  Email: huj@hope.ac.uk 
Kun Yang           School  of  Computer  Science  &  Electronic  Engineering, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom
                              Tel: +44 1206 872449 Email: kunyang@essex.ac.uk 
Chirag Warty     Chief  Technologist,  Ahilya  Technologies,  Los  Angeles, California, USA
                               Email: chiragwarty@ieee.org 
Ke Xu                   Department  of  Computer  Science,  Tsinghua  University, Beijing, P. R. China
                              Tel: +86 10 6260 3056  Email: xuke@tsinghua.edu.cn
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