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- W2951133144 abstract "Real-world networks are prone to breakdowns. Typically in the underlying graph $G$, besides the insertion or deletion of edges, the set of active vertices changes overtime. A vertex might work actively, or it might fail, and gets isolated temporarily. The active vertices are grouped as a set $S$. $S$ is subjected to updates, i.e., a failed vertex restarts, or an active vertex fails, and gets deleted from $S$. Dynamic subgraph connectivity answers the queries on connectivity between any two active vertices in the subgraph of $G$ induced by $S$. The problem is solved by a dynamic data structure, which supports the updates and answers the connectivity queries. In the general undirected graph, the best results for it include $widetilde{O}(m^{2/3})$ deterministic amortized update time, $widetilde{O}(m^{4/5})$ and $widetilde{O}(sqrt{mn})$ deterministic worst-case update time. In the paper, we propose a randomized data structure, which has $widetilde{O}(m^{3/4})$ worst-case update time." @default.
- W2951133144 created "2019-06-27" @default.
- W2951133144 creator A5072926038 @default.
- W2951133144 creator A5074195634 @default.
- W2951133144 date "2016-11-28" @default.
- W2951133144 modified "2023-09-26" @default.
- W2951133144 title "Faster Randomized Worst-Case Update Time for Dynamic Subgraph Connectivity" @default.
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- W2951133144 doi "https://doi.org/10.48550/arxiv.1611.09072" @default.
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