A Survey on Enhanced MapReduce Spatial Hadoop in Cloud Computing

Authors

  • N Vetrivelan Professor, Periyar Maniammai University, Tamilnadu.
  • C Jasmin Selvi Ph.D Research Scholar, Bharathiyar University, Tamilnadu

Keywords:

Cloud Computing, Hadoop, HDFS, MapReduce

Abstract

Cloud Computing is creating as a new computational worldview shift. Hadoop-MapReduce has become a powerful Calculation Model alternately handling huge information on Dispersed thing equipment groups such as Clouds. In all Hadoop implementations, the shortcoming FIFO scheduler is accessible where employments are booked in FIFO request with support alternately other Need based schedulers also. In this paper we study distinctive scheduler changes conceivable with Hadoop and too given some guidelines on how to improve the Planning in Hadoop in Cloud Environments.

References

S. Narkhede; T. Baraskar; D. Mukhopadhyay, “Analyzing web application log files to find hit count through the utilization of Hadoop MapReduce in cloud computing environment”, IT in Business, Industry and Government (CSIBIG), 2014 Conference on Year: 2014 Pages: 1 – 7.

P. Gohil; D. Garg; B. Panchal, “A performance analysis of MapReduce applications on big data in cloud based Hadoop”, Information Communication and Embedded Systems (ICICES), 2014 International Conference on Year: 2014 Pages: 1 – 6.

D. Garg; K. Trivedi, “Fuzzy K-mean clustering in MapReduce on cloud based hadoop”, Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on Year: 2014 Pages: 1607 – 1610.

W. Premchaiswadi; W. Romsaiyud; S. Intarasema;, “Applying Hadoop's MapReduce framework on clustering the GPS signals through cloud computing”, High Performance Computing and Simulation (HPCS), 2013 International Conference on Year: 2013 Pages: 644 – 649.

J. George; C. A. Chen; R. Stoleru; G. G. Xie; T. Sookoor; D. Bruno, “Hadoop MapReduce for Tactical Clouds” Cloud Networking (CloudNet), 2014 IEEE 3rd International Conference on Year: 2014 Pages: 320 – 326.

Downloads

Published

2025-11-11

How to Cite

[1]
N. Vetrivelan and C. Jasmin Selvi, “A Survey on Enhanced MapReduce Spatial Hadoop in Cloud Computing”, Int. J. Comp. Sci. Eng., vol. 4, no. 4, pp. 266–271, Nov. 2025.

Issue

Vol. 4 No. 4 (2016): IJCSE April Edition

Section

Survey Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.