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Cloud Computing: Principles and Paradigms
Abstract
The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications. We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it. This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level. As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field.
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Citations
Cited by
The Use of MQTT in M2M and IoT Systems: A Survey
Mishra, B., & Kertesz, A. (2020) · IEEE Access · doi:10.1109/access.2020.3035849 · Cited by 429
A systematic review on effective energy utilization management strategies in cloud data centers
Panwar, S. S., Rauthan, M. M. S., & Barthwal, V. (2022) · Journal of Cloud Computing · doi:10.1186/s13677-022-00368-5 · Cited by 65
Metadata
- Venue
- Wiley eBooks
- Publisher
- Wiley
- Published
- 2011-01-03
- OpenAlex
- W4245256586
- Cited by
- 453
- References
- 0
- FWCI
- 18.56
- Type
- book
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.