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Erschienen in:
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2024 | OriginalPaper | Buchkapitel

4. Cloud Computing for Big Data Analytics

verfasst von : Ümit Demirbaga, Gagangeet Singh Aujla, Anish Jindal, Oğuzhan Kalyon

Erschienen in: Big Data Analytics

Verlag: Springer Nature Switzerland

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Abstract

In this chapter, the exploration unfolds within the domain of cloud computing, emphasising its instrumental role in empowering the realm of big data analytics. Commencing with a comprehensive exposition, the historical evolution of cloud computing is meticulously traced across various computing generations, culminating in its contemporary manifestation as a transformative and indispensable component of the Information Technology (IT) landscape. Subsequently, cloud computing service models are systematically elucidated in conjunction with an exhaustive examination of deployment models, including public, private, hybrid, and community clouds. Furthermore, multi-cloud strategies are explored, with an in-depth exploration of key cloud computing platforms. A thorough comparison of these renowned cloud providers is offered to aid in making well-informed decisions and provide stakeholders with the necessary knowledge to effectively use cloud computing’s promise to enhance big data analytics.

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Vorheriges Kapitel Big Data Analytics
Nächstes Kapitel Big Data Analytics Platforms
Fußnoten
Literatur
1.
K. Hwang, J. Dongarra, G.C. Fox, Distributed and Cloud Computing: From Parallel Processing to the Internet of Things. (Morgan kaufmann, 2013)
2.
R. Ranjan, I.S. Thakur, G.S. Aujla, N. Kumar, A.Y. Zomaya, Energy-efficient workflow scheduling using container-based virtualization in software-defined data centers. IEEE Trans. Ind. Inf. 16(12), 7646–7657 (2020)CrossRef
3.
R. Prodan, E. Torre, J.J. Durillo, G.S. Aujla, N. Kummar, H.M. Fard, S. Benedikt, Dynamic multi-objective virtual machine placement in cloud data centers, in 2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) (2019), pp. 92–99
4.
C. Yang, Q. Huang, Z. Li, K. Liu, F. Hu, Big data and cloud computing: innovation opportunities and challenges. Int. J. Digital Earth 10(1), 13–53 (2017)CrossRef
5.
Y. Lu, X. Xu, Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services. Robot. Comput. Integr. Manufact. 57, 92–102 (2019)CrossRef
6.
F. Habeeb, K. Alwasel, A. Noor, D.N. Jha, D. AlQattan, Y. Li, G.S. Aujla, T. Szydlo, R. Ranjan, Dynamic bandwidth slicing for time-critical iot data streams in the edge-cloud continuum. IEEE Trans. Ind. Inf. 18(11), 8017–8026 (2022)CrossRef
7.
K.A. Kumar et al., Big data characteristics, classification and challenges-a review. Turkish J. Comput. Math. Edu. (TURCOMAT) 12(12), 4236–4243 (2021)
8.
Z.N. Rashid, S.R. Zebari, K.H. Sharif, K. Jacksi, Distributed cloud computing and distributed parallel computing: A review, in 2018 International Conference on Advanced Science and Engineering (ICOASE). (IEEE, 2018), pp. 167–172
9.
J. Dean, S. Ghemawat, Mapreduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)CrossRef
10.
U. Demirbaga, D.N. Jha, Social media data analysis using mapreduce programming model and training a tweet classifier using apache mahout, in IEEE 8th International Symposium on Cloud and Service Computing (SC2). (IEEE, 2018), pp. 116–121
11.
R. Vaupel, High Availability and Scalability of Mainframe Environments using System z and z/OS as Example. (KIT Scientific Publishing, 2014)
12.
A.R. Lebeck, X. Fan, H. Zeng, C. Ellis, Power aware page allocation. ACM SIGARCH Comput. Architect. News 28(5), 105–116 (2000)CrossRef
13.
M. Revett, I. Boyd, C. Stephens, Network computing: a tutorial review. Electron. Commun. Eng. J. 13(1), 5–15 (2001)CrossRef
14.
A. Sunyaev, A. Sunyaev, Internet Computing. (Springer, 2020)
15.
J. Joseph, C. Fellenstein, Grid Computing. (Prentice Hall Professional, 2004)
16.
D. Georgakopoulos, P.P. Jayaraman, M. Fazia, M. Villari, R. Ranjan, Internet of things and edge cloud computing roadmap for manufacturing. IEEE Cloud Comput. 3(4), 66–73 (2016)CrossRef
17.
M.U. Bokhari, Q.M. Shallal, Y.K. Tamandani, Cloud computing service models: A comparative study, in 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom). (IEEE, 2016), pp. 890–895
18.
R. Buyya, J. Broberg, A.M. Goscinski, Cloud Computing: Principles and Paradigms. (John Wiley & Sons, 2010)
19.
A. Yousif, M. Farouk, M.B. Bashir, A cloud based framework for platform as a service, in 2015 International Conference on Cloud Computing (ICCC). (IEEE, 2015), pp. 1–5
20.
D. Dziembek, T. Turek, Characteristics and application of unified communications as a service (ucaas) in enterprises. Inform. Ekonomiczna 4(50), 47–65 (2018)CrossRef
21.
G. Laatikainen, A. Ojala, Saas architecture and pricing models, in 2014 IEEE International Conference on Services Computing. (IEEE, 2014), pp. 597–604
22.
V. Kundra, State of Public Sector Cloud Computing (Federal Chief Information, 2010)
23.
M. Olowu, C. Yinka-Banjo, S. Misra, H. Florez, A secured private-cloud computing system, in Applied Informatics: Second International Conference, ICAI, Madrid, Spain, November 7–9, 2019, Proceedings 2. (Springer, 2019), pp. 373–384
24.
A. Srinivasan, M.A. Quadir, V. Vijayakumar, Era of cloud computing: A new insight to hybrid cloud. Procedia Comput. Sci. 50, 42–51 (2015)CrossRef
25.
A. Marinos, G. Briscoe, Community cloud computing, in Cloud Computing: First International Conference, CloudCom (Beijing, China, December 1–4, 2009). Proceedings 1. Springer 2009, 472–484 (2009)
26.
J. Hong, T. Dreibholz, J.A. Schenkel, J.A. Hu, An overview of multi-cloud computing, in Web, Artificial Intelligence and Network Applications: Proceedings of the Workshops of the 33rd International Conference on Advanced Information Networking and Applications (WAINA-2019) 33. (Springer, 2019), pp. 1055–1068
27.
28.
29.
30.
R. Ranjan, K. Mitra, P.P. Jayaraman, L. Wang, A.Y. Zomaya, Handbook of Integration of Cloud Computing, Cyber Physical Systems and Internet of Things. (Springer, 2020)
31.
M. Trovati, R. Hill, A. Anjum, S. Ying Zhu, L. Liu, Big-data Analytics and Cloud Computing. (Springer, 2015)
Metadaten
Titel
Cloud Computing for Big Data Analytics
verfasst von
Ümit Demirbaga
Gagangeet Singh Aujla
Anish Jindal
Oğuzhan Kalyon
Copyright-Jahr
2024
Buch
Big Data Analytics

Print ISBN: 978-3-031-55638-8

Electronic ISBN: 978-3-031-55639-5

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-3-031-55639-5_4

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