Performance of Approximate Causal Consistency for Partially Replicated Systems

Abstract

Causal consistency is one of the widely used consistency models in wide-area replicated systems due to highly scalable semantics. Partial replication is a replication mechanism that emphasizes a better network capacity utilization. However, it has a challenge of higher meta-data overhead and processing complexity in communication. Algorithm Approx-Opt-Track has been proposed to reduce meta-data size, however, by risking that causal consistency might be violated. In an effort to bridge this gap and reconcile the trade-off between them, we present the analytic data to show the performance of Approx-Opt-Track. We also give simulation results to show the potential benefits of Approx-Opt-Track, under almost the same guarantees as causal consistency, at a smaller cost. The results indicate that partial replication is a potentially viable alternative to full replication for implementing causal consistency.