DocumentCode :
3537700
Title :
Accelerating Biomedical Data-Intensive Applications Using MapReduce
Author :
Han, Liangxiu ; Ong, Hwee Yong
Author_Institution :
Manchester Metropolitan Univ., Manchester, UK
fYear :
2012
fDate :
20-23 Sept. 2012
Firstpage :
49
Lastpage :
57
Abstract :
In this paper, we investigate how MapReduce and Cloud computing can accelerate performance of applications and scale up the computing resources through a real data mining use case in the Biomedical Sciences. We have prototyped the data mining task using the MapReduce model and evaluated it in the Cloud. A performance evaluation model has been built for assessing the eff ciency of the prototype. The results, from both experiments and the evaluation model, show the performance and scalability can be enhanced through these advanced technologies.
Keywords :
cloud computing; data mining; medical computing; software performance evaluation; MapReduce model; biomedical data-intensive applications; biomedical sciences; cloud computing; computing resources; data mining; performance evaluation model; Conferences; Grid computing; Tunneling magnetoresistance; Cloud computing; Data mining application in Biomedical Science; MapReduce; Parallel processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid Computing (GRID), 2012 ACM/IEEE 13th International Conference on
Conference_Location :
Beijing
ISSN :
1550-5510
Print_ISBN :
978-1-4673-2901-9
Type :
conf
DOI :
10.1109/Grid.2012.24
Filename :
6319154
Link To Document :
بازگشت