Self-optimising Application-agnostic Multithreading for Replicated State Machines

State-machine replication (SMR) is a well-known approach for fault-tolerant services demanding fast recovery. It is not easy, however, to parallelise SMR in order to exploit modern multicore architectures. Two main approaches have been extensively studied; one focusing on request-level concurrency using prior knowledge, the other utilising application-agnostic and lock-level deterministic scheduling. We show that significant performance improvements for the latter approach require deterministic scheduler configurations to be dynamically adapted to the current application load during runtime. First, we summarise current research on parallel SMR execution. Second, an analysis of obstacles in lock-level deterministic multithreading approaches shows how static scheduler configurations can lead to poor performance when load on the system varies over time. Third, we present a simple yet effective automatic adaptation solution, which provides significantly better overall system behaviour compared to static configurations. This is demonstrated by evaluations using a full system setup.