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Cloud and Big Data Electronic Age: A Review

by Muneeba Afzal Mukhdoomi, Ashish Oberoi, Ankur Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 37
Year of Publication: 2020
Authors: Muneeba Afzal Mukhdoomi, Ashish Oberoi, Ankur Gupta
10.5120/ijca2020920941

Muneeba Afzal Mukhdoomi, Ashish Oberoi, Ankur Gupta . Cloud and Big Data Electronic Age: A Review. International Journal of Computer Applications. 175, 37 ( Dec 2020), 32-43. DOI=10.5120/ijca2020920941

@article{ 10.5120/ijca2020920941,
author = { Muneeba Afzal Mukhdoomi, Ashish Oberoi, Ankur Gupta },
title = { Cloud and Big Data Electronic Age: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 37 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 32-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number37/31693-2020920941/ },
doi = { 10.5120/ijca2020920941 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:32.083810+05:30
%A Muneeba Afzal Mukhdoomi
%A Ashish Oberoi
%A Ankur Gupta
%T Cloud and Big Data Electronic Age: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 37
%P 32-43
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big data stands for sheer amount of data that is growing unceasingly at a rapid pace. Big Data demands high-powered, robust, reliable, fault-tolerant tools and techniques in order to make it convenient to process, analyse and uproot new insights from Big Data. Big data refers to huge, heterogeneous amount of details, facts and data generating at constantly rising rate. The data sets in Big Data are too bulky or extensive, as a result classical data handling application software are not competent enough to administer them. On the other hand, Cloud computing is a resourceful technology providing high computing power, scalability, computing resources as and when required for processing, storage, analytics and visualization of Big Data. Therefore, cloud computing can be regarded as a feasible and applicable technology which promises to handle Big Data challenges and also provides here and now infrastructures with all the mandatory resources. This paper will mainly review processing of big data using Hadoop and spark in cloud, advantages of driving Big Data using cloud computing and applications of Big data in Cloud.

References
  1. S. Kaisler, F. Armour, J. A. Espinosa, and W. Money, “Big data: Issues and challenges moving forward,” Proc. Annu. Hawaii Int. Conf. Syst. Sci., pp. 995–1004, 2013, doi: 10.1109/HICSS.2013.645.
  2. M. Islam and S. Reza, “The Rise of Big Data and CloudComputing,” Internet Things Cloud Comput., vol. 7, no. 2, p. 45, 2019, doi: 10.11648/j.iotcc.20190702.12.
  3. R. L. Villars, C. W. Olofson, and M. Eastwood, “Big Data: What It is and Why You Should Care,” IDC White Pap., pp. 7–8, 2011.
  4. I. A. T. Hashem, I. Yaqoob, N. B. Anuar, S. Mokhtar, A. Gani, and S. Ullah Khan, “The rise of ‘big data’ on cloud computing: Review and open research issues,” Inf. Syst., vol. 47, pp. 98–115, 2015, doi: 10.1016/j.is.2014.07.006.
  5. Mayer-Schonberger, V., & Cukier, K. Big data.
  6. M. A. U. D. Khan, M. F. Uddin, and N. Gupta, “Seven V’s of Big Data understanding Big Data to extract value,” Proc. 2014 Zo. 1 Conf. Am. Soc. Eng. Educ. - “Engineering Educ. Ind. Involv. Interdiscip. Trends”, ASEE Zo. 1 2014, 2014, doi: 10.1109/ASEEZone1.2014.6820689
  7. J. Hurwitz, A. Nugent, F. Halper, and M. Kaufman, Big Data for Dummies, no. 1. 2013.
  8. Retrieved from https://en.wikipedia.orglwikiCloud_computing.asp
  9. V. V. Arutyunov, “Cloud computing: Its history of development, modern state, and future considerations,” Sci. Tech. Inf. Process., vol. 39, no. 3, pp. 173–178, 2012, doi: 10.3103/S0147688212030082.
  10. V. Kale and V. Kale, “Cloud Computing Basics,” Creat. Smart Enterp., no. August 2013, pp. 141–171, 2017, doi: 10.1201/9781315152455-6.
  11. Retrieved from https://www.investopedia.com/terms/c/cloud-computing.asp
  12. Guo, H., Goodchild, M., & Annoni, A. Manual of Digital Earth.
  13. Shawish A., Salama M. (2014) Cloud Computing: Paradigms and Technologies. In: Xhafa F., Bessis N. (eds) Inter-cooperative Collective Intelligence: Techniques and Applications. Studies in Computational Intelligence, vol 495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35016-0_2
  14. B. P. Rimal, E. Choi, and I. Lumb, “A taxonomy and survey of cloud computing systems,” NCM 2009 - 5th Int. Jt. Conf. INC, IMS, IDC, pp. 44–51, 2009, doi: 10.1109/NCM.2009.218.
  15. S. Namasudra, P. Roy, and B. Balusamy, “Cloud computing: Fundamentals and research issues,” Proc. - 2017 2nd Int. Conf. Recent Trends Challenges Comput. Model. ICRTCCM 2017, pp. 7–12, 2017, doi: 10.1109/ICRTCCM.2017.49.
  16. Mell, P., & Grance, T. (2020). The NIST definition of cloud computing.
  17. L. Savu, “Cloud computing: Deployment models, delivery models, risks and research challanges,” 2011 Int. Conf. Comput. Manag. CAMAN 2011, 2011, doi: 10.1109/CAMAN.2011.5778816.
  18. Y. Jadeja and K. Modi, “Cloud computing - Concepts, architecture and challenges,” 2012 Int. Conf. Comput. Electron. Electr. Technol. ICCEET 2012, pp. 877–880, 2012, doi: 10.1109/ICCEET.2012.6203873.
  19. Z. Tang, “On Study of Application of Big Data and Cloud Computing Technology in Smart Campus On Study of Application of Big Data and Cloud Computing Technology in Smart Campus,” 2017, doi: 10.1088/1755-1315/.
  20. Retrieved from https://www.oreilly.com/libabry/view/moving-hadoop-to-/9781491959626/ch01.html
  21. Retrieved from https://blog.syncsort.com/2017/06/bigdata/5-reasons-hadoop –in-the-cloud
  22. D. Tomar and P. Tomar, "Integration of Cloud Computing and Big Data Technology for Smart Generation," 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, 2018, pp. 1-6, doi: 10.1109/CONFLUENCE.2018.8443052.
  23. J. Hurwitz, A. Nugent, F. Halper, and M. Kaufman, Big Data for Dummies, no. 1. 2013.
  24. .Z. Han and Y. Zhang, “Spark: A Big Data Processing Platform Based on Memory Computing,” Proc. - Int. Symp. Parallel Archit. Algorithms Program. PAAP, vol. 2016-Janua, pp. 172–176, 2016, doi: 10.1109/PAAP.2015.41
  25. M. Franklin, “The Berkeley Data Analytics Stack: Present and future,” pp. 2–3, 2014, doi: 10.1109/bigdata.2013.6691545.
  26. M. Mittal and V. E. Balas, Big Data Processing Using Spark in Cloud. 2018.
  27. R. Ilijason, Beginning Apache Spark Using Azure Databricks. 2020.
  28. K. Alwasel, R. N. Calheiros, S. Garg, R. Buyya, and R. Ranjan, “BigDataSDNSim: A Simulator for Analyzing Big Data Applications in Software-Defined Cloud Data Centers,” 2019, [Online]. Available: http://arxiv.org/abs/1910.04517.
  29. Q. Zhang, L. T. Yang, Z. Chen, and P. Li, “PPHOPCM: Privacy-preserving High-order Possibilistic c-Means Algorithm for Big Data Clustering with Cloud Computing,” IEEE Trans. Big Data, vol. 7790, no. c, pp. 1–1, 2017, doi: 10.1109/tbdata.2017.2701816.
  30. H. Pargmann, D. Euhausen, and R. Faber, “Intelligent big data processing for wind farm monitoring and analysis based on cloud-Technologies and digital twins: A quantitative approach,” 2018 3rd IEEE Int. Conf. Cloud Comput. Big Data Anal. ICCCBDA 2018, pp. 233–237, 2018, doi: 10.1109/ICCCBDA.2018.8386518.
  31. V. Vashishth, A. Chhabra, and A. Sood, “A predictive approach to task scheduling for Big Data in cloud environments using classification algorithms,” Proc. 7th Int. Conf. Conflu. 2017 Cloud Comput. Data Sci. Eng., pp. 188–192, 2017, doi: 10.1109/CONFLUENCE.2017.7943147.
  32. Lu Qu, R., 2017. big data and cloud computing for energy internet. (china) international Electrical and energy confrence,.
  33. Y. Zhang, J. Ren, J. Liu, C. Xu, H. Guo, and Y. Liu, “A survey on emerging computing paradigms for big data,” Chinese J. Electron., vol. 26, no. 1, pp. 1–12, 2017, doi: 10.1049/cje.2016.11.016.
  34. S. Nepal and M. V Ramakrishna, “Proceedings of the International Conference on Data Engineering,” pp. 22–31, 1999, doi: 10.1007/978-981-10-1678-3.
  35. S. Rallapalli, G. Rr, U. Pavan, and K. Ketavarapu, “Impact of Processing and Analyzing Healthcare Big Data on Cloud Computing Environment by Implementing Hadoop Cluster,” Procedia - Procedia Comput. Sci., vol. 85, pp. 16–22, 2016, doi: 10.1016/j.procs.2016.05.171.
  36. L. Kuang, L. T. Yang, and Y. Liao, “An Integration Framework on Cloud for Cyber-Physical-Social Systems Big Data,” IEEE Trans. Cloud Comput., vol. 8, no. 2, pp. 363–374, 2020, doi: 10.1109/TCC.2015.2511766.
  37. K. Kedharewsari, V. Maria Anu, and V. Rajalakshmi, “Integration of big data & cloud computing to detect black money rotation with range - aggregate queries,” Int. J. Eng. Technol., vol. 8, no. 2, pp. 768–773, 2016, doi: 10.18535/ijecs/v5i6.23.
  38. V. N. Inukollu, S. Arsi, and S. Rao Ravuri, “Security Issues Associated with Big Data in Cloud Computing,” Int. J. Netw. Secur. Its Appl., vol. 6, no. 3, pp. 45–56, 2014, doi: 10.5121/ijnsa.2014.6304.
  39. L. Zhang, C. Wu, Z. Li, C. Guo, M. Chen, and F. C. M. Lau, “Moving big data to the cloud: An online cost-minimizing approach,” IEEE J. Sel. Areas Commun., vol. 31, no. 12, pp. 2710–2721, 2013,doi: 10.1109/JSAC.2013.131211.
  40. R. Schmidt and M. Möhring, “Strategic alignment of cloud-based architectures for big data,” Proc. - IEEE Int. Enterp. Distrib. Object Comput. Work. EDOC, pp. 136–143, 2013, doi: 10.1109/EDOCW.2013.22.
  41. The future of big data: 5 predictions from experts for 2020-2025. (2020). ,retrieved from https://www.itransition.com/blog/the-future-of-big-data
  42. Casestudy,CloudComputing(CLOUD),2010,in:Proceedingsof IEEE 3rd International Conferenceon,IEEE,Miami,FL,2010, pp. 107–114.
  43. S. A. El-seoud, H. F. El-sofany, M. Ashraf, and F. Abdelfattah, “Big Data and Cloud Computing?: Trends and Challenges Big Data and Cloud Computing?: Trends and Challenges,” no. April, 2017, doi: 10.3991/ijim.v11i2.6561.
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Hadoop MapReduce Spark cloud computing

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