Conflict Managers for Self-stabilization without Fairness Assumption

In this paper, we specify the conflict manager abstraction. Informally, a conflict manager guarantees that any two nodes that are in conflict cannot enter their critical section simultaneously (safety), and that at least one node is able to execute its critical section (progress). The conflict manager problem is strictly weaker than the classical local mutual exclusion problem, where any node that requests to enter its critical section eventually does so (fairness). We argue that conflict managers are a useful mechanism to transform a large class of self-stabilizing algorithms that operate in an essentially sequential model, into self-stabilizing algorithm that operate in a completely asynchronous distributed model. We provide two implementations (one deterministic and one probabilistic) of our abstraction, and provide a composition mechanism to obtain a generic transformer. Our transformers have low overhead: the deterministic transformer requires one memory bit, and guarantees time overhead in order of the network degree, the probabilistic transformer does not require extra memory. While the probabilistic algorithm performs in anonymous networks, it only provides probabilistic stabilization guarantees. In contrast, the deterministic transformer requires initial symmetry breaking but preserves the original algorithm guarantees.