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Challenges of Crowd Sensing for Cost-Effective Data Management in the Cloud

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Cloud Computing and Big Data: Technologies, Applications and Security (CloudTech 2017)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 49))

Abstract

Cloud computing has attracted researchers and organizations in the last decade due to the powerful and elastic computation capabilities provided on-demand to users. Mobile cloud computing is a way of enriching users of mobile devices with the computational resources and services of clouds. The recent developments of mobile devices and their sensors introduced the crowd sensing paradigm that uses powerful cloud computing to analyze, manage and store data produced by mobile sensors. However, crowd sensing in the context of using the cloud is posing new challenges that increase the importance of adopting new approaches to overcome them. This chapter introduces a middleware solution that provides a set of services for cost-effective management of crowd sensing data.

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Acknowledgements

Aseel Alkhelaiwi’s research is funded by King Saud University in Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science, University College Cork, Cork, Ireland

    Aseel Alkhelaiwi & Dan Grigoras

Authors
  1. Aseel Alkhelaiwi
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  2. Dan Grigoras
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Corresponding authors

Correspondence to Aseel Alkhelaiwi or Dan Grigoras .

Editor information

Editors and Affiliations

  1. ENSIAS College of Engineering, Mohammed V University, Agdal, Rabat, Morocco

    Mostapha Zbakh

  2. ENSIAS College of Engineering, Mohammed V University, Agdal, Rabat, Morocco

    Mohammed Essaaidi

  3. Department of Computer Science, Polytechnic of Mons, Mons, Belgium

    Pierre Manneback

  4. Department of Electrical Engineering and Computer Science, University of Stavanger, Stavanger, Norway

    Chunming Rong

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Alkhelaiwi, A., Grigoras, D. (2019). Challenges of Crowd Sensing for Cost-Effective Data Management in the Cloud. In: Zbakh, M., Essaaidi, M., Manneback, P., Rong, C. (eds) Cloud Computing and Big Data: Technologies, Applications and Security. CloudTech 2017. Lecture Notes in Networks and Systems, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-97719-5_6

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