A Predictive Multi-Tenant Database Migration and Replication in the Cloud Environment

Abstract

With the rapid adoption of multi-tenant databases, the cloud provider consolidates multiple tenants’ database on server machines, where the tenants share a common application and database instances. To ensure the quality of service (QoS) for the leased resources, both sides (i.e., the user and the provider) create a Service Level Agreement (SLA). Higher SLA violations result in high SLA contractual penalties and increase the possibility of losing the tenant. In addition, the unusual workload patterns of each tenant transactions require seamless adjustments due to the sudden burden changes and variability. As a result, to satisfy simultaneously availability and performance tenant requirements, it is necessary to perform reliable tenant migration and replication to distribute the workload to a flexible set of sites and avoid SLA violations. In this research, a cluster-based multi-tenant database management system (CB-MT DBMS) is proposed, which takes the migration and replication decisions in advance by monitoring and acting before the violation of the SLA occurs. In addition, a dynamic proactive multi-tenant database migration and replication MTDB-MR algorithm is proposed to reduce collisions and inconsistencies between migration and replication decisions for a group of violated tenants. Experimental results show that the proposed MTDB-MR algorithm is the ideal candidate for migration and replication of the violated multi-tenant databases, as it minimizes the total number of SLA violations, the number of multi-tenant clients SLA violations, client sites average response time and total execution time of each multi-tenant client site as compared to the previous algorithms.

Keywords

• Cloud computing
• data migration
• data replication
• service level agreements SLA
• TPC benchmarks