A dynamic Tenant-Defined Storage system for efficient resource management in cloud applications

In this article, we present a dynamic and extensible system for the management of storage resources in multi-tenant cloud applications. In the presented approach, tenants are hierarchically clustered based on multiple scenario-specific characteristics, and allocated to storage resources using a hierarchical bin packing algorithm (static allocation). As the load changes over time, the system corresponds to these changes by reallocating storage resources when required (dynamic reallocation). We evaluate both the static and dynamic behavior of our system. Experiments confirm that the system achieves good results regarding the average bin usage, migrations over time and clustering of related tenants. On average, less than 0.01% of the total amount of data is reallocated during each migration using the dynamic Hierarchical First-Fit Decreasing (dHFFD) algorithm while achieving an average bin usage similar to First-Fit Decreasing (FFD). The dynamic Hierarchical Greedy Decreasing (dHGD) algorithm reduces the number of migrations by a factor 100 compared to dHFFD, but at the cost of provisioning additional storage instances.