Update of applications in SaaS is expected to be a continuous efforts and cannot be done overnight or over the weekend. In such migration efforts, users are trained and shifted from one existed version to another new version successively. There is a long period of time when both versions of applications co-exist. Maintenance of two systems with both existed and new version at the same time is not a cost efficient option and such two systems may suffer from slow response time due to continuous synchronization with each other. In this paper, we focus on how to enable the migration of enterprise applications in SaaS via progressive evolved schema. Instead of maintenance with two systems, our solution is to build a multi-version applications supported system by designing an series of intermediate schemas which are optimized for mixed workloads from both existed and emerging users. With an application migration schedule, an genetic algorithm is used to find out the more effective intermediated schema as well as migration paths and schedule. A key advantage of our approach is optimum performance during the long migration period while maintaining the same level of data movement required by the migration. We evaluated the proposed progressive migration approach on a TPCW benchmark and experimental results validated its effectiveness of across a variety of scenarios. They demonstrate that the schema evolution based application migration could bring about 200% performance gain comparing to the systems with either existed old version or targeted new version.
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- Enabling Migration of Enterprise Applications in SaaS via Progressive Schema Evolution
- Springer Berlin Heidelberg
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