Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain

Abstract This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance efficiency of reaching consensus. Specifically, novel concept with confidence interval (PLTS-CI) is presented express uncertain complex voting information nodes during election. Then, score function exponential semantic value and approximation PLTS-CI, called Score-ESCA, used solve problems comparing different various attitudes. helps select highest by utilizing decision attitudes, making it an accurate solution. Furthermore, feasibility our proposed proved both theoretical analysis experimental evaluations.