Cloud Computing for Big Data Analysis

Encyclopedia of Big Data Technologies

Abstract

NA

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Similar content being viewed by others

References

  • Agapito G, Cannataro M, Guzzi PH, Marozzo F, Talia D, Trunfio P (2013) Cloud4snp: distributed analysis of snp microarray data on the cloud. In: Proc. of the ACM conference on bioinformatics, computational biology and biomedical informatics 2013 (ACM BCB 2013). ACM Press, Washington, DC, p 468. ISBN 978-1-4503-2434-2

    Google Scholar 

  • Altomare A, Cesario E, Comito C, Marozzo F, Talia D (2017) Trajectory pattern mining for urban computing in the cloud. Trans Parallel Distrib Syst 28(2):586–599. ISSN:1045-9219

    Google Scholar 

  • Belcastro L, Marozzo F, Talia D, Trunfio P (2015) Programming visual and script-based big data analytics workflows on clouds. In: Big data and high performance computing, advances in parallel computing, vol 26. IOS Press, pp 18–31

    Google Scholar 

  • Belcastro L, Marozzo F, Talia D, Trunfio P (2016) Using scalable data mining for predicting flight delays. ACM Trans Intell Syst Technol 8(1):1–20

    Article  Google Scholar 

  • Belcastro L, Marozzo F, Talia D, Trunfio P (2017) A parallel library for social media analytics. In: The 2017 international conference on high performance computing & simulation (HPCS 2017). Genoa, Italy, pp 683–690, ISBN: 978-1-5386-3250-5

    Chapter  Google Scholar 

  • Belcastro L, Marozzo F, Talia D, Trunfio P (2018) G-roi: automatic region-of-interest detection driven by geotagged social media data. ACM Trans Knowl Discovery Data 12(3):27:1–27:22

    Google Scholar 

  • Belcastro L, Marozzo F, Talia D (2019a) Programming models and systems for big data analysis. Int J Parallel Emergent Distrib Syst 34:632–652

    Article  Google Scholar 

  • Belcastro L, Marozzo F, Talia D, Trunfio P (2019b) Develo** a cloud-based algorithm for analyzing the polarization of social media users. In: 5th international symposium, ALGOCLOUD 2019, Munich, Germany

    Google Scholar 

  • Dean J, Ghemawat S (2004) Mapreduce: Simplified data processing on large clusters. In: Proceedings of the 6th conference on symposium on operating systems design & implementation, vol 6, Berkeley, USA, OSDI’04, pp 10–10

    Google Scholar 

  • Gu Y, Grossman RL (2009) Sector and sphere: the design and implementation of a high-performance data cloud. Philos Trans R Soc Lond A: Math Phys Eng Sci 367(1897):2429–2445

    Google Scholar 

  • Hiden H, Woodman S, Watson P, Cala J (2013) Develo** cloud applications using the e-science central platform. Philos Trans R Soc A 371(1983):20120, 085

    Google Scholar 

  • Kang U, Chau DH, Faloutsos C (2012) Pegasus: Mining billion-scale graphs in the cloud. In: 2012 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 5341–5344, https://doi.org/10.1109/ICASSP.2012.6289127

  • Li A, Yang X, Kandula S, Zhang M (2010) Cloudcmp: comparing public cloud providers. In: Proceedings of the 10th ACM SIGCOMM conference on Internet measurement, ACM, New York, pp 1–14

    Google Scholar 

  • Lin H, Lin Z, Diaz JM, Li M, An H, Gao GR (2019) swflow: a dataflow deep learning framework on sunway taihulight supercomputer. In: 2019 IEEE 21st international conference on high performance computing and communications; IEEE 17th international conference on smart city; IEEE 5th international conference on data science and systems (HPCC/SmartCity/DSS). IEEE, pp 2467–2475

    Google Scholar 

  • Lordan F, Tejedor E, Ejarque J, Rafanell R, Ãlvarez J, Marozzo F, Lezzi D, Sirvent R, Talia D, Badia R (2014) ServiceSs: an interoperable programming framework for the cloud. J Grid Comput 12(1):67–91

    Article  Google Scholar 

  • Marozzo F, Talia D, Trunfio P (2015) Js4cloud: script-based workflow programming for scalable data analysis on cloud platforms. Concurrency Comput Practice Exp 27(17):5214–5237

    Article  Google Scholar 

  • Marozzo F, Talia D, Trunfio P (2016) A workflow management system for scalable data mining on clouds. IEEE Trans Serv Comput 11(3):480–492

    Article  Google Scholar 

  • Martin A, Brito A, Fetzer C (2016) Real-time social network graph analysis using streammine3g. In: Proceedings of the 10th ACM international conference on distributed and event-based systems. ACM, New York, NY, USA, DEBS ’16, pp 322–329

    Google Scholar 

  • Mell PM, Grance T (2011) Sp 800-145. the nist definition of cloud computing. Tech. rep., National Institute of Standards & Technology, Gaithersburg, MD, United States

    Google Scholar 

  • Richardson L, Ruby S (2008) RESTful web services.O’Reilly Media

    Google Scholar 

  • Talia D (2019) A view of programming scalable data analysis: from clouds to exascale. J Cloud Comput 8(1):4

    Article  Google Scholar 

  • Talia D, Trunfio P, Marozzo F (2015) Data analysis in the cloud. Elsevier, Amsterdam. ISBN: 978-0-12-802881-0

    Google Scholar 

  • Talia D, Trunfio P, Marozzo F, Belcastro L, Garcia Blas J, Del Rio D, Couvée P, Goret G, Vincent L, Fernández Pena A, Martin de Blas D, Nardi M, Pizzuti T, Spataru A, Justyna M (2019) A novel data-centric programming model for large-scale parallel systems. In: Euro-Par workshops

    Google Scholar 

  • Tejedor E, Becerra Y, Alomar G, Queralt A, Badia RM, Torres J, Cortes T, Labarta J (2017) Pycompss: parallel computational workflows in python. Int J High Perform Comput Appl 31(1):66–82

    Article  Google Scholar 

  • Wiewirka MS, Messina A, Pacholewska A, Maffioletti S, Gawrysiak P, Okoniewski MJ (2014) SparkSeq: fast, scalable and cloud-ready tool for the interactive genomic data analysis with nucleotide precision. Bioinformatics 30(18):2652–2653. https://doi.org/10.1093/bioinformatics/btu343

    Article  Google Scholar 

  • Yakneen S, Waszak SM, Gertz M, Korbel JO (2020) Butler enables rapid cloud-based analysis of thousands of human genomes. Nat Biotechnol 38(3):288–292

    Article  Google Scholar 

  • You L, Motta G, Sacco D, Ma T (2014) Social data analysis framework in cloud and mobility analyzer for smarter cities. In: 2014 IEEE international conference on service operations and logistics, and informatics (SOLI), pp 96–101

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fabrizio Marozzo .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this entry

Cite this entry

Marozzo, F., Belcastro, L. (2022). Cloud Computing for Big Data Analysis. In: Zomaya, A., Taheri, J., Sakr, S. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_136-2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63962-8_136-2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63962-8

  • Online ISBN: 978-3-319-63962-8

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Cloud Computing for Big Data Analysis
    Published:
    14 February 2018

    DOI: https://doi.org/10.1007/978-3-319-63962-8_136-1

  2. Original

    Cloud Computing for Big Data Analysis
    Published:
    24 February 2012

    DOI: https://doi.org/10.1007/978-3-319-63962-8_136-2

Navigation