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Erschienen in:
Elliptic Curve Qu-Vanstone Based Signcryption Schemes with Proxy Re-encryption for Secure Cloud Data Storage Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

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

verfasst von : Aseel Alkhelaiwi, Dan Grigoras

Erschienen in: Cloud Computing and Big Data: Technologies, Applications and Security

Verlag: Springer International Publishing

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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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Vorheriges Kapitel Issues and Threats of Cloud Data Storage
Nächstes Kapitel On the Security of Medical Image Processing in Cloud Environment
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Metadaten
Titel
Challenges of Crowd Sensing for Cost-Effective Data Management in the Cloud
verfasst von
Aseel Alkhelaiwi
Dan Grigoras
Copyright-Jahr
2019
Buch
Cloud Computing and Big Data: Technologies, Applications and Security

Print ISBN: 978-3-319-97718-8

Electronic ISBN: 978-3-319-97719-5

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-97719-5_6

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