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SULTAN: A Composite Data Consistency Approach for SaaS Multi-Cloud Deployment

Elgedawy, Islam
Migrating business services to the clouds creates many high business risks such as "cloud vendor lock-in". One approach for preventing this risk is to deploy business services on different clouds as SaaS (i.e., Software as a Service) services. Unfortunately, such SaaS multi-cloud deployment approach faces many technical obstacles such as clouds heterogeneity and ensuring data consistency across different clouds. Cloud heterogeneity could be easily resolved using service adapters, but ensuring data consistency remains a major obstacle, as existing approaches offer a trade-off between correctness and performance. Hence, SaaS providers opt to choose one or more of these approaches at design time, then create their services based on the limitations of the chosen approaches. This approach limits the agility and evolution of business services, as it tightly couples them to the chosen data consistency approaches. To overcome such problem, this paper proposes SULTAN, a composite data consistency approach for SaaS multi-cloud deployment. It enables SaaS providers to dynamically define different data consistency requirements for the same SaaS service at run-time. SULTAN decouples the SaaS services from the cloud data stores, enabling services to adapt and migrate freely among clouds without any SaaS code modifications.