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Mobile and Ubiquitous Systems: Computing, Networking, and Services. 9th International Conference, MobiQuitous 2012, Beijing, China, December 12-14, 2012. Revised Selected Papers

Research Article

Honeybee: A Programming Framework for Mobile Crowd Computing

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  • @INPROCEEDINGS{10.1007/978-3-642-40238-8_19,
        author={Niroshinie Fernando and Seng Loke and Wenny Rahayu},
        title={Honeybee: A Programming Framework for Mobile Crowd Computing},
        proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 9th International Conference, MobiQuitous 2012, Beijing, China, December 12-14, 2012. Revised Selected Papers},
        proceedings_a={MOBIQUITOUS},
        year={2013},
        month={9},
        keywords={mobile crowd computing mobile cloud computing remote execution offloading crowd sourcing},
        doi={10.1007/978-3-642-40238-8_19}
    }
    
  • Niroshinie Fernando
    Seng Loke
    Wenny Rahayu
    Year: 2013
    Honeybee: A Programming Framework for Mobile Crowd Computing
    MOBIQUITOUS
    Springer
    DOI: 10.1007/978-3-642-40238-8_19
Niroshinie Fernando1,*, Seng Loke1,*, Wenny Rahayu1,*
  • 1: La Trobe University
*Contact email: tnfernando@students.latrobe.edu.au, s.loke@latrobe.edu.au, w.rahayu@latrobe.edu.au

Abstract

Although smartphones are increasingly becoming more and more powerful, enabling pervasiveness is severely hindered by the resource limitations of mobile devices. The combination of social interactions and mobile devices in the form of ‘crowd computing’ has the potential to surpass these limitations. In this paper, we introduce Honeybee; a crowd computing framework for mobile devices. Honeybee enables mobile devices to share work, utilize local resources and human collaboration in the mobile context. It employs ‘work stealing’ to effectively load balance tasks across nodes that are a priori unknown. We describe the design of Honeybee, and report initial experimental data from applications implemented using Honeybee.

Keywords
mobile crowd computing mobile cloud computing remote execution offloading crowd sourcing
Published
2013-09-24
http://dx.doi.org/10.1007/978-3-642-40238-8_19
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