Efficient transformation of distance-2 self-stabilizing algorithms

Self-stabilizing algorithms for optimization problems can often be solved more easily using the distance-two model in which each vertex can instantly see the state information of all vertices up to distance two. This paper presents a new technique to emulate algorithms for the distance-two model on the distance-one model using the distributed scheduler with a slowdown factor of O(m)$O\left(m\right)$ moves. Up until now the best transformer had a slowdown factor of O(n²m)$O\left(n^{2}m\right)$ moves. The technique is used to derive improved self-stabilizing algorithms for several graph domination problems. The paper also introduces a generalization of the distance-two model allowing a more space efficient transformer.