This paper deals with the trade-off between time, workload, and versatility in self-stabilization, a general and lightweight fault-tolerant concept in distributed computing.In this context, we propose a transformer that provides an asynchronous silent self-stabilizing version Trans(AlgI) of any terminating synchronous algorithm AlgI. The transformed algorithm Trans(AlgI) works under the distributed unfair daemon and is efficient both in moves and rounds.Our transformer allows to easily obtain fully-polynomial silent self-stabilizing solutions that are also asymptotically optimal in rounds.We illustrate the efficiency and versatility of our transformer with several efficient (i.e., fully-polynomial) silent self-stabilizing instances solving major distributed computing problems, namely vertex coloring, Breadth-First Search (BFS) spanning tree construction, k-clustering, and leader election.

翻译：本文研究了自稳定（一种分布式计算中通用且轻量级的容错概念）中时间、工作量和通用性之间的权衡。在此背景下，我们提出一种转换器，可为任意终止型同步算法AlgI生成异步静默自稳定版本Trans(AlgI)。转换后的算法Trans(AlgI)可在分布式非公平调度器下运行，并在移动次数和轮数上均保持高效。该转换器使我们能够轻松获得完全多项式级的静默自稳定解决方案，且在轮数上渐进最优。我们通过多个高效的（即完全多项式级的）静默自稳定实例，证明了转换器的效率和通用性，这些实例解决了主要的分布式计算问题，包括顶点着色、广度优先搜索（BFS）生成树构建、k-聚类和领导者选举。