Causal broadcasting and consistency of distributed shared data

The paper develops a generalized model to capture the interactions between the ordering of messages exchanged across various entities of a distributed application and the consistency requirements on a shared data across these entities. The model is based on causal broadcasting of data access messages that allows messages to be ordered at all entities as per the constraints specified by the application. This allows each entity to change its local data copy based on the messages processed and still be in agreement with other entities at selected points of message exchanges that are meaningful to the application, which we refer to as stable points in the underlying execution. Since the causal relationships among messages depict an invariant property of the application and stable points are reproducible across different execution instances, application-specific consistency of the data can be enforced in many cases without explicit protocols to reach agreement. The model of integrating causality with data consistency allows more flexibility in the implementation of data access protocols for distributed services and offers potential for increased performance of the protocols