Data Based Application Partitioning and Workload Balance in Distributed Environment

Many application partitioning methods have been proposed based on different functional modules in distributed environment to gain efficient use of resources, improved performance and high scalability. This paper introduces popular application partitioning architectures, and presents a different partitioning method and an on-line workload balance algorithm from a new perspective: runtime data, called data based application partitioning. This architecture benefits applications with higher performance, scalability and dynamic workload balancing. A financial trading system reengineered from J2EE standalone environment into data partitioning distributed environment gives a nice proof.