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Scalable Data Processing for Community Sensing Applications

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Abstract

Participatory Sensing is a new computing paradigm that aims to turn personal mobile devices into advanced mobile sensing networks. For popular applications, we can expect a huge number of users to both contribute with sensor data and request information from the system. In such scenario, scalability of data processing becomes a major issue. In this paper, we present a system for supporting participatory sensing applications that leverages cluster or cloud infrastructures to provide a scalable data processing infrastructure. We propose and evaluate three strategies for data processing in this architecture.

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  1. Groovy is a dynamic, object-oriented programming language that runs on top of the Java Virtual Machine and includes DSL design features.

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Acknowledgements

We would like to thank the anonymous reviewers for their helpful comments. This work was supported partially by project #PTDC/EIA/76114/2006 and PEst-OE/EEI/UI0527/2011—CITI/FCT/UNL/2011–12.

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Authors and Affiliations

  1. CITI - Departamento de Informática Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Quinta da Torre, 2829 -516, Caparica, Portugal

    Sérgio Duarte, David Navalho, Heitor Ferreira & Nuno Preguiça

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  1. Sérgio Duarte
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  2. David Navalho
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  3. Heitor Ferreira
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  4. Nuno Preguiça
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Correspondence to Sérgio Duarte.

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Duarte, S., Navalho, D., Ferreira, H. et al. Scalable Data Processing for Community Sensing Applications. Mobile Netw Appl 18, 357–372 (2013). https://doi.org/10.1007/s11036-012-0424-9

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