Abstract:
Online transaction Processing (OLTP) applications are business applications which are characterized by high-frequency short lived data transactions. In cloud domain, applications are expected to be highly responsive and low cost with optimized levels of consistency. Cloud data stores rely on an appropriate data partitioning scheme to achieve promising levels of responsiveness and scalability. This work presents a novel, transaction aware, static, vertical data partitioning scheme based on denormalization which performs well for OLTP applications in cloud domain. The scheme is implemented and tested on contemporary cloud data stores i.e Amazon SimpleDB and Hadoop HBase. Our work also proposes a mathematical specification model for TAVPD based data partitioning and suggests appropriate evaluation factors for a data partitioning scheme in cloud database.
Page(s):
73-81
DOI:
DOI not available
Published:
Journal: Journal of Theoretical and Applied Information Technology, Volume: 59, Issue: 1, Year: 2014