2015/05/01 by Jean-Paul Bahsoun, Rachid Guerraoui, Ali Shoker · 1 citation
Computer Science · Engineering · #Distributed systems and fault tolerance #Software System Performance and Reliability #Radiation Effects in Electronics #Computer science #Protocol (science) #Distributed computing #Robustness (evolution) #Throughput #Process (computing) #Set (abstract data type) #Communications protocol #Computer network #Operating system
paper · doi:10.1109/ipdps.2015.21
openalex publication_date 2015/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
Many state-machine Byzantine Fault Tolerant (BFT) protocols have been introduced so far. Each protocol addressed a different subset of conditions and use-cases. However, if the underlying conditions of a service span different subsets, choosing a single protocol will likely not be a best fit. This yields robustness and performance issues which may be even worse in services that exhibit fluctuating conditions and workloads. In this paper, we reconcile existing state-machine BFT protocols in a single adaptive BFT system, called ADAPT, aiming at covering a larger set of conditions and use-cases, probably the union of individual subsets of these protocols. At anytime, a launched protocol in ADAPT can be aborted and replaced by another protocol according to a potential change (an event) in the underlying system conditions. The launched protocol is chosen according to an "evaluation process" that takes into consideration both: protocol characteristics and its performance. This is achieved by applying some mathematical formulas that match the profiles of protocols to given user (e.g., service owner) preferences. ADAPT can assess the profiles of protocols (e.g., throughput) at run-time using Machine Learning prediction mechanisms to get accurate evaluations. We compare ADAPT with well known BFT protocols showing that it outperforms others as system conditions change and under dynamic workloads.