A belated proof of self-stabilization
Distributed Computing
Closure and Convergence: A Foundation of Fault-Tolerant Computing
IEEE Transactions on Software Engineering - Special issue on software reliability
Resource discovery in distributed networks
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Deterministic resource discovery in distributed networks
Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures
Corona: a stabilizing deterministic message-passing skip list
SSS'11 Proceedings of the 13th international conference on Stabilization, safety, and security of distributed systems
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Distributed cooperative computing in networks involves marshaling collections of network nodes possessing the necessary computational resources. Before the willing nodes can act in a concerted way they must first discover one another. This is the general setting of the Resource Discovery Problem (RDP). This paper presents a self-stabilizing algorithm that solves RDP in a deterministic synchronous setting. The solution approach is formulated in terms of evolving knowledge graphs, where vertices represent the participating network nodes, and edges represent one node's knowledge about another. Ideally, the diameter of such a graph is one, i.e., each node knows all others. The algorithm works in rounds as it evolves the knowledge graph with the goal of reducing its diameter. This is accomplished by nodes sharing their knowledge through gossip messages. We prove that the algorithm is self-stabilizing, i.e., it tolerates arbitrary perturbations in the nodes' local states and is guaranteed to solve the problem once such failures subside. The algorithm has stabilization time of O(D), and it takes at most 4D + 4 complete round to stabilize, where D is the diameter of the initial knowledge graph, and the corresponding message complexity is O,(|V|j ⋅D), where V is the set of participating nodes.