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cc 14(1): e6

Research Article

MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

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  • @ARTICLE{10.4108/cc.1.1.e6,
        author={Prem Prakash  Jayaraman and Charith Perera and Dimitrios Georgakopoulos and Arkady Zaslavsky},
        title={MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications},
        journal={EAI Endorsed Transactions on Collaborative Computing},
        volume={1},
        number={1},
        publisher={ICST},
        journal_a={CC},
        year={2014},
        month={5},
        keywords={opportunistic sensing, crowdsensing, mobile middleware, mobile data analytics},
        doi={10.4108/cc.1.1.e6}
    }
    
  • Prem Prakash Jayaraman
    Charith Perera
    Dimitrios Georgakopoulos
    Arkady Zaslavsky
    Year: 2014
    MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications
    CC
    ICST
    DOI: 10.4108/cc.1.1.e6
Prem Prakash Jayaraman1,*, Charith Perera1, Dimitrios Georgakopoulos2, Arkady Zaslavsky1
  • 1: CSIRO Computational Informatics, Canberra, Australia 2601
  • 2: School of Computer Science and Information Technology, RMIT University, GPO Box 2476, Melbourne VIC 3001
*Contact email: prem.jayaraman@csiro.au

Abstract

Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data acrossmultiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.

Keywords
opportunistic sensing, crowdsensing, mobile middleware, mobile data analytics
Received
2014-03-04
Accepted
2014-04-28
Published
2014-05-27
Publisher
ICST
http://dx.doi.org/10.4108/cc.1.1.e6

Copyright © 2014 P.P Jayaraman, et al., licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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