EFFICIENT BIG DATA ANALYSIS USING HADOOP FRAMEWORK FOR SENSOR NETWORK DATA

Article Sidebar

PDF
Published: Jun 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i3.6105
Keywords:
Big data, Hadoop, Wireless Sensor Network

Main Article Content

Sahana. R

Abstract

In the era of rapid development of the technology, Wireless Sensor Networks is also a field that is been developing and already reached  a stage where thousands of nodes in a network will be present and they store and also deliver a vast amount of data. We are living in the age where an explosive amount of data is being generated every day. Majorly the data from sensors, mobile devices, social networking websites, scientific data & enterprises are contributing to a maximum extent for this huge explosion of data. The major problem will be the amount of data collected, its storage and processing. So in an order to store, load and process the large scale sensory data we propose a paper that enable the efficient and effective analysis of the Big Data and also handling the large volumes carried out on the Hadoop platform.

 

Downloads

Download data is not yet available.

Article Details

Issue
Vol. 9 No. 3 (2018): May - June 2018
Section
Articles

COPYRIGHT

Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
  • The journal allows the author(s) to retain publishing rights without restrictions.
  • The journal allows the author(s) to hold the copyright without restrictions.

References

Gurpreet Singh Bedi, Ashima Singh, Big Data Analysis with Dataset Scaling in Yet another Resource Negotiator (YARN), International Journal of Computer Applications (0975–8887) Volume 92 –No.5, April2014

Bing Tang and Yu Wang ,Design of Large-Scale Sensory Data Processing System Based on Cloud Computing, , School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China, College of Computer and Information Engineering, Honai University, Research Journal of Applied Sciences, Engineering and Technology ISSN: 2040- 7467, © Maxwell Scientific Organization,2012

Han hui ,yong gang wen, tat- seng chual , and xuelongli, Toward Scalable Systems for Big Data Analytics: A Technology Tutorial, October 2013.

Mandar Mokashi, Dr.A.S.Alvi ,Data Management in Wireless Sensor Network: A Survey- IJARCCE, Vol. 2, Issue 3, March 2013.

PraveenKumar, Dr Vijay Singh Rathore Efficient Capabilities of Processing of Big Data using Hadoop Map Reduce-, IJARCCE, Vol. 3, Issue 6, June 2014

X. Wu, X. Zhu, G. Wu, and W. Ding, Transactions onKnowledge and Data Engineering, Data mining with big data, vol. 99, June2013.

Vodel and W. Hardt, Data aggregation in resource-limited wireless communication environments - differences between theory and praxis, M. in Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS2012). Ho Chi Minh City, Vietnam: IEEE Computer Society, November 2012, pp.282–287.

D. Laney, Gartner, The Importance of ’Big Data’: A Definition. 2012.

S.Madden, R. Szewczyk, M. J. Franklin, and D. Culler ,Supporting Aggregate Queries Over Ad-Hoc Wireless Sensor Networks, ,in Proceedings Fourth IEEE Workshop on Mobile Computin Systems and Applications, 2002.

M. J. Millerand N. H. Vaidya,Minimizing energy consumption in sensor networks using a wakeup radio, in Proceedings of the Wireless Communications and Networking Conference. WCNC. 2004 IEEE, vol. a, March 2004, pp.2335– 2340.

Chair of Computer Engineering, Technische Universit¨at Chemnitz, “Planet – platform for ambient networking,â€

www.ce.informatik.tuchemnitz.de/forschung/demonst ratoren/planet/, September2013.

M. Vodel, R. Bergelt, and W. Hardt, A generic data processing framework for heterogeneous sensor-actor-networks, , International Journal On Advances in Intelligent Systems, vol. Vol. 4, December 2012.

hortonworks.com/products/hortonworks-sandbox-URL

M. Ceriotti ,Monitoring heritage buildings with wireless sensor networks: The Torre Aquila deployment,., in Proc. Int. Conf. Inform. Process. Sensor Netw., Apr. 2009,pp. 277–288.

F. Gallagher,The Big Data Value Chain [Online],.Available:http://fraysen.blogspot.sg/2012/06/big-data-value-chain.html(2013)

M. Sevilla.Big Data Vendors and Technologies, the list! [Online], Available: http://www.capgemini.com/blog/capping- off/2012/09/big-data-vendors-a%nd-technologies. (2012).