Egophobic Voting Algorithms

Abstract

Approximate agreement is one form of distributed agreement, in which the processes in executing a voting algorithm are required to agree on values that are very close to each other. Recent studies have partitioned the voting algorithms into three broad categories: anonymous, egocentric, and egophobic. Among these categories, Egophobic algorithms have not yet been studied. This article considers one family of Egophobic algorithms. They are studied under a hybrid-fault model consisting of asymmetric, symmetric, and benign faults. We obtain their convergence rate and fault-tolerance expressions, show that these algorithms cannot discriminate between asymmetric and symmetric faults, and compare their performance against that of algorithms in other categories. The study of Egophobic algorithms will further research into forming a unified model capable of addressing any algorithms in these categories.