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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 

Content
 

Volumes > Volume 7 > No. 1

 
   

Data Migration from Grid to Cloud Computing

PP: 399-406
Author(s)
Wei Chen, Kuo-Cheng Yin, Don-Lin Yang, Ming-Chuan Hung,
Abstract
The advance of information and communication technologies over the last decade has improved the quality of healthcare and medical services tremendously. Especially, the people living in the countryside or remote areas benefit the most from telemedicine and emergency services. Our Health Grid is one of the test beds which provide various health-related Web services associated with mobile devices and physiological data acquisition and analysis instruments. As the number of new applications being developed increases rapidly, the ever-growing volume of collected data and real-time demand of analysis result have driven the architectural migration from Grid to Cloud Computing much sooner than we expected. Our challenge is to make the transition cost effective. This paper describes the data access migration from a relational database to Apache’s HBase - one of the cloud databases. Our contribution is to minimize the required change of software for data access. Since the SQL commands of the relational database cannot be used in HBase, various mechanisms for translation and mapping between two sides must be developed. In addition, the services provided by the Web programs in Health Grid are written in various kinds of Web language while HBase does not support the access authority to these Web languages. To reduce the effort of modifying the source code for accessing HBase, we propose the use of Web services as the communication interface between various Web programs and necessary facilities to execute SQL commands in HBase. Although this is a hard engineering work, our results show that the proposed approaches are feasible and cost effective for the development teams at academic institutes. With this preliminary study, our next step is to improve our methods to take advantage of the efficient functions of HBase in processing the large amount of data.

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