Software-as-a-Service (SaaS) is a new software delivery model with Multi-Tenancy Architecture (MTA). An SaaS system is often mission critical as it often supports a large number of tenants, and each tenant supports a large number of users. This paper proposes a scalable index management algorithm based on B+ tree but with automated redundancy and recovery management as the tree maintains two copies of data. The redundancy and recovery management is done at the SaaS level as data are duplicated with tenant information rather than at the PaaS level where data are duplicated in chunks. Using this approach, an SaaS system can scale out or in based on the dynamic workload. This paper also uses tenant similarity measures to cluster tenants in a multi-level scalability architecture where similar tenants can be grouped together for effcient processing. The scalability mechanism also includes an automated migration strategies to enhance the SaaS performance. The proposed scheme with automated recovery and scalability has been simulated, the results show that the proposed algorithm can scale well with increasing workloads.
Wei-Tek Tsai, Guanqiu Qi, Zhiqin Zhu. Scalable SaaS Indexing Algorithms with Automated Redundancy and Recovery Management. International Journal of Software and Informatics, 2013,7(1):63~84Copy