Trading replication consistency for performance and availability: an adaptive approach

Replication system is one of the most fundamental building blocks of wide-area applications. Due to the inevitable dependencies on wide-area communication, trade-off between performance, availability and replication consistency is often a necessity. While a number of proposals have been made to provide a tunable consistency bound between strong and weak extremes, many of them rely on a statically specified enforcement across replicas. This approach, while easy to implement, neglects the dynamic contexts within which replicas are operating, delivering sub-optimal performance and/or system availability. In this paper we analyze the problem of optimal performance/availability for a given consistency level under heterogeneous workload and network condition. We prove several optimization rules for different goals. Based on these results, we developed an adaptive update window protocol in which consistency enforcement across replicas is self-tuned to achieve optimal performance/availability. A prototype system, FRACS, is built and evaluated in this paper. The experiment results demonstrate significant advantages of adaptation over static approach for a variety of workloads.