DCfRSM: Fault-Tolerant checkpoint approach for replicated state machines

Abstract

As a result of attractive offers including serverless hosting services by cloud vendors, usage of state machine models has been widely spread in various areas in terms of software development for cloud. Serverless computing phenomenon offers software developers not only eliminating the need to take care of many aspects of software development stack but also focusing on developing main tasks to be executed by cloud system. Using state machine models in order to express the required functionality in one of the popular approaches for serverless computing. Cloud vendors also offers non functional requirements such as fault tolerance, integrability, etc. Replicating a single state machine across cluster which is going to work in distributed manner with the aim of handling requests is very well-known approach for providing fault tolerance. With other words, a major approach that can be used in fault tolerance is checkpointing. Checkpointing offers saving the system state in specific frequencies in order to boot the system back in case of any failure. Especially, applying different checkpointing approaches in replicated state machine systems is an highly active research topic for today's cloud computing era. In this thesis, advantages of splitting snapshots of replicated state machine images with the aim of decreasing memory overhead during persisting the system context is investigated.