Optimized Image Processing using Big Data Dynamic Handover Reduce Function (DHRF) in Cloud - Review
Keywords:
Hadoop, MapReduce, DHRF, Euca2ool, Cloud ComputingAbstract
Processing of hard task like this can be solves by using the concept of Hadoop, Map Reduce .Hadoop is a framework that allows to process and store huge data sets. Map Reduce is a programming model which allows you to process huge data stored in hadoop. Map is a concept of splitting or dividing data and Reduce function is the process of integrating the output of Map’s input to produce the result. The Map function does two various image processing techniques to process the input data. Java Advanced Imaging (JAI) is introduced in the map function .The processed intermediate data of the Map function is sent to the reduce function for further process. The Dynamic Handover Reduce function (DHRF) algorithm is introduced in the Reduce function. This algorithm gives final output by processing the Reduce function. MapReduce concept and proposed optimized algorithm is made to work on Euca2ool(cloud tool) to produce an effective and better output compared to previous tasks in field of Big data and cloud computing.
References
- Jyoti S.Patil,G.Pradeepani,”Two Dimensional Medical Images Diagnosis using MapReduce”,pp 1-5, Volume 9 (17), May 2016
- Nauman Sheikh, “Chapter 11 Big Data, Hadoop, and Cloud Computing, Implementing Analytics A Blueprint for Design, Development, and Adoption”, Pages 185–197, Publication Year 2013.
- Sweeney, C. Liu, L., Arietta, S., Lawrence, J. HIPI: A Hadoop Image Processing Interface for Image-based MapReduce Tasks. B.S. thesis, University of Virginia (2011)
- HaoYu, “FAST corner detection-Machine learning for high speed corner detection”, Publication Year 2010
- Lalit malik, sunita sagwan”,Mapreduce framework implementation on the prescritptive Analysis of healh Industry”,Vol 4,Issue 6,pp 675-688,june 2015.
- Wang Zhongye,Yang Xiaohui,Niu Hongjuan”,Brushlet domainretrival algorithum based on complex computer simulation of image texture characteristics, pp 263-266 ,2011.
- T. White, MapReduce: The Definitive Guide. O'Reilly Media, Yahoo! Press, June 5, 2009M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 1989
- B. Li, H. Zhao, Z. H. Lv, “Parallel ISODATA clustering of remote sensing images based on Map Reduce,” in 2010 Int. Conf. Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC).
- T. White, Hadoop: The Definitive Guide. O'Reilly Media, Yahoo! Press, June 5, 2009.
- HaoYu, “FAST corner detection-Machine learning for high speed corner detection”, Publication Year 2010.
- Patel, A.B. ; Birla, M. ; Nair, U., “Addressing big data problem using Hadoop and Map Reduce, Engineering (NUiCONE)”, Nirma University International Conference on Digital Object Identifier, 10.1109/NUICONE.2012.6493198 Page(s), 1 – 5, 2012
- Hyeokju Lee, Myoungjin Kim, Joon Her, and Hanku Lee, “Implementation of MapReduce-based Image ConversionModule in Cloud Computing Environment”, 978-1-4673-0250-0/12/$31.00 ©2012 IEEE.
- Balachandar S., Chinnaiyan R. (2019) Centralized Reliability and Security Management of Data in Internet of Things (IoT) with Rule Builder. In: Smys S., Bestak R., Chen JZ., Kotuliak I. (eds) International Conference on Computer Networks and Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 15. Springer, Singapore
- Balachandar S., Chinnaiyan R. (2019) Reliable Digital Twin for Connected Footballer. In: Smys S., Bestak R., Chen JZ., Kotuliak I. (eds) International Conference on Computer Networks and Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 15. Springer, Singapore
- Druv patel , Rahul seth, vikas Mishra” real -time bus tracking sysyem “ international research journal of engineering and technology volume: 04 issue :03 – march -2017.
- Mohammed F. Alrifaie, Norharyati Harum, MohdFairuzIskandar Othman, IrdaRoslan, Methaq Abdullah Shyaa,“vehical detection and tracking system iot based”, International research journal of engineering and techanology volume:05 isuue: 08 – aug 2018
- S. Balachandar, R. Chinnaiyan (2019), Internet of Things Based Reliable Real-Time Disease Monitoring of Poultry Farming Imagery Analytics, Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 31), 615- 620. Springer, Cham
- S.Balachandar , R.Chinnaiyan (2018), A Reliable Troubleshooting Model for IoT Devices with Sensors and Voice Based Chatbot Application, International Journal for Research in Applied Science & Engineering Technology,Vol.6,Iss.2, 1406-1409.
- S.Balachandar , R.Chinnaiyan (2018), Centralized Reliability and Security Management of Data in Internet of Things (IoT) with Rule Builder, Lecture Notes on Data Engineering and Communications Technologies 15, 193-201.
- S.Balachandar , R.Chinnaiyan (2018), Reliable Digital Twin for Connected Footballer, Lecture Notes on Data Engineering and Communications Technologies 15, 185-191.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRST
This work is licensed under a Creative Commons Attribution 4.0 International License.