Distributed View Divergence Control of Data Freshness in Replicated Database Systems

In this paper, we propose a distributed method to control the view divergence of data freshness for clients in replicated database systems whose facilitating or administrative roles are equal. Our method provides data with statistically defined freshness to clients when updates are initially accepted by any of the replicas, and then, asynchronously propagated among the replicas that are connected in a tree structure. To provide data with freshness specified by clients, our method selects multiple replicas using a distributed algorithm so that they statistically receive all updates issued up to a specified time before the present time. We evaluated by simulation the distributed algorithm to select replicas for the view divergence control in terms of controlled data freshness, time, message, and computation complexity. The simulation showed that our method achieves more than 36.9 percent improvement in data freshness compared with epidemic-style update propagation.