Introduction to Bigdata and Relation with IoT

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Big Data consist of large scale data which is complicated and diverse, so that new and different types of integration of techniques and technologies are required to uncover various hidden values from such big datasets. Big Data surrounding is used to set up and examine the diverse sorts of information. Big Data be data that is so massive in volume, so various in range or moving with excessive speed is referred to as Big Data. Acquiring and analysing Big Data be a challenging job because it consists of large dispersed file systems which must be bendy, fault tolerant and scalable. Diverse technologies used by big data application toward hold the huge quantity of data are Hadoop, Map Reduce, and so on. In this paper, firstly the description of big dataset is provided. In next section the different technologies are described which are used for managing Big Data. After that, Big Data method application and in last section we discuss the relation of Big Data and IoT as well as IoT for Big Data analytics.



  • Keywords

    Big data, Hadoop , MapReduce, Internet of Things, Analytics.

  • References

      [1] Tasleem Nizam and Syed Imtiyaz Hassan, “Big Data: A Survey Paper on Big Data Innovation and its Technology,” in International Journal of Advanced Research in Computer Science, Vol.8, No. 5, pp. 2173–2177, 2017.

      [2] C. Lakshmi and V. V. Nagendra Kumar “Survey Paper on Big Data,” in International Journal of Advanced Research in Computer Science and Software Engineering, vol.6, No. 8, pp. 368-381, 2016.

      [3] Yuri Demchenko, “The Big Data Architecture Framework (BDAF)”, Outcome of the Brainstorming Session at the University of Amsterdam 17 July 2013.

      [4] Amogh Pramod Kulkarni, Mahesh Khandewal, “Survey on Hadoop and Introduction to YARN”, International Journal of Emerging Technology and Advanced Engineering Website: (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 5, May 2014).

      [5] M. R. Berthold, N. Cebron, F. Dill, T. R. Gabriel, T. Kötter, T. Meinl, et al., “KNIME: The Konstanz Information Miner”, in Data Analysis, Machine Learning and Applications (Studies in Classification, Data Analysis, and Knowledge Organization), Springer Berlin Heidelberg, pp. 319–326, 2008.

      [6] Sagiroglu, S.Sinanc, D.,”Big Data: A Review”,2013, 20-24.

      [7] Ms. Vibhavari Chavan, Prof. Rajesh and N. Phursule, “Survey Paper On Big Data”, International Journal of Computer Science and Information Technologies, Vol. 5 (6), 2014.

      [8] Samiddha Mukherjee and Ravi Shaw, “Big Data – Concepts, Applications, Challenges and Future Scope”, International Journal of Advanced Research in Computer and Communication Engineering, 2016.

      [9] Hua Fang, Zhaoyang Zhang, ChanpaulJin Wang, Mahmoud Deshmand, Chonggang Wang, and HonggangWang, “A Survey of Big Data Research”, IEEE Network, 2015.

      [10]KuchipudiSravanthi and TatireddySubba Reddy, “Applications of Big Data in Various Fields”, International Journal of Computer Science and Information Technology, 2015.

      [11]D. P. Acharjya, Kauser Ahmed P, “A Survey on Big Data Analytics: Challenges, OpenResearch Issues and Tools”, International Journal of Advanced Computer Science and Applications, Vol. 7, No. 2, 2016.

      [12]Anjali Deore, Bhayashree More, Kaveri Sonawane, Jyoti Kharat, “Introduction to Hadoop Architecture and Installation on Ubantu”, International Journal of Research in Engineering and Technology, Vol. 6, issue 9, 2017.




Article ID: 16851
DOI: 10.14419/ijet.v7i3.8.16851

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.