Research And Application On Load Balance Of Data Based Application Partitioning

High-throughput, high performance, high availability and high stability become the four main categories to determine the system quality as the enterprise applications progress. Moreover, because people more and more rely on the fast computing ability, enterprise applications enter a new era of distributed environment from the standalone box episode. However, the classic software architecture, symmetric software architecture and asymmetric software architecture cannot the meet the current requirements. They are complex, huge, utilizing the computing resources in a bad way and the data transmission become a production bottleneck. So they cannot provide enough supports for high performance, high availability and high scalability.In this thesis, based on the symmetric and asymmetric software architecture, we present a new software architecture—data based application partitioning in distributed environment. It adopts the advantages from both symmetric and asymmetric software architectures; process request data according to the data partitions, and largely improve the performance of data transmission.Secondly, based on the load balance theory, we propose a self-adaptive load balancing method based on structured P2P protocol, successfully resolved load balancing issues under the framework of the data partition. And the load balance algorithm is well proved by our simulation program.Then, we apply data based software architecture to a large production system of a globalized company. This case study, including the architecture, performance and scalability test results shows the benefits of data partition software architecture.Last, a conclusion of software architecture and load balance in data based application partitioning is given, which is followed by the reference, publication list and thanks.