Proof-labeling schemes are known mechanisms providing nodes of networks with certificates that can be verified locally by distributed algorithms. Given a boolean predicate on network states, such schemes enable to check whether the predicate is satisfied by the actual state of the network, by having nodes interacting with their neighbors only. Proof-labeling schemes are typically designed for enforcing fault-tolerance, by making sure that if the current state of the network is illegal with respect to some given predicate, then at least one node will detect it. Such a node can raise an alarm, or launch a recovery procedure enabling the system to return to a legal state. In this paper, we introduce error-sensitive proof-labeling schemes. These are proof-labeling schemes which guarantee that the number of nodes detecting illegal states is linearly proportional to the edit-distance between the current state and the set of legal states. By using error-sensitive proof-labeling schemes, states which are far from satisfying the predicate will be detected by many nodes, enabling fast return to legality. We provide a structural characterization of the set of boolean predicates on network states for which there exist error-sensitive proof-labeling schemes. This characterization allows us to show that classical predicates such as, e.g., acyclicity, and leader admit error-sensitive proof-labeling schemes, while others like regular subgraphs don't. We also focus on compact error-sensitive proof-labeling schemes. In particular, we show that the known proof-labeling schemes for spanning tree and minimum spanning tree, using certificates on $O(\log n)$ bits, and on $O\left(\log^2n\right)$ bits, respectively, are error-sensitive, as long as the trees are locally represented by adjacency lists, and not just by parent pointers.
翻译:校对标签机制是已知的机制,它提供网络节点,其证书可在本地通过分布式算法进行验证。在网络状态上,这种机制能够通过只与邻居进行节点互动,检查上游是否为网络实际状态所满足。 校对标签机制通常是为了执行过错容忍度而设计的。 通过使用对错误敏感的校对标签机制,确保网络当前状态对于某个给定的上游是非法的,然后至少有一个节点会检测它。 这种节点可以引起警示,或者启动一个恢复程序( 敏锐性地让系统返回到合法状态 ) 。 在本文中,我们引入了对错误敏感的校对标签机制。 通过使用对错误敏感的Oralalal 规则, 并且通过许多节点, 能够快速恢复到合法性。 在网络状态上, 我们提供了一个对布利安的定位机制进行结构性的描述, 并且可以显示对错误敏感的Oliver 的标签方案。