Multi-consistency Data Replication

Abstract

Replication is a technique widely used in parallel and distributed systems to provide qualities such as performance, scalability, reliability and availability to their clients. These qualities comprise the non-functional requirements of the system. But the functional requirement consistency may also get affected as a side-effect of replication. Different replica control protocols provide different levels of consistency from the system. In this paper we present the middleware based McRep replication protocol that supports multiple consistency model in a distributed system with replicated data. Both correctness criteria and divergence aspects of a consistency model can be specified in the McRep configuration. Supported correctness criteria include linearizability, sequential consistency, serializability, snapshot isolation and causal consistency. Bounds on divergence can be specified in either version metric or delay metric. Our approach allows the same middleware to be used for applications requiring different consistency guarantees, eliminating the need for mastering a new replication middleware or framework for every application. We carried out experiments to compare the performance of various consistency requirements in terms of response time, concurrency conflict and bandwidth overhead. We demonstrate that in McRep workloads only pay for the consistency guarantees they actually need.