Emergent Mind

Abstract

We consider dynamic algorithms for maintaining Single-Source Reachability (SSR) and approximate Single-Source Shortest Paths (SSSP) on $n$-node $m$-edge directed graphs under edge deletions (decremental algorithms). The previous fastest algorithm for SSR and SSSP goes back three decades to Even and Shiloach [JACM 1981]; it has $ O(1) $ query time and $ O (mn) $ total update time (i.e., linear amortized update time if all edges are deleted). This algorithm serves as a building block for several other dynamic algorithms. The question whether its total update time can be improved is a major, long standing, open problem. In this paper, we answer this question affirmatively. We obtain a randomized algorithm with an expected total update time of $ O(\min (m{7/6} n{2/3 + o(1)}, m{3/4} n{5/4 + o(1)}) ) = O (m n{9/10 + o(1)}) $ for SSR and $(1+\epsilon)$-approximate SSSP if the edge weights are integers from $ 1 $ to $ W \leq 2{\logc{n}} $ and $ \epsilon \geq 1 / \logc{n} $ for some constant $ c $. We also extend our algorithm to achieve roughly the same running time for Strongly Connected Components (SCC), improving the algorithm of Roditty and Zwick [FOCS 2002]. Our algorithm is most efficient for sparse and dense graphs. When $ m = \Theta(n) $ its running time is $ O (n{1 + 5/6 + o(1)}) $ and when $ m = \Theta(n2) $ its running time is $ O (n{2 + 3/4 + o(1)}) $. For SSR we also obtain an algorithm that is faster for dense graphs and has a total update time of $ O ( m{2/3} n{4/3 + o(1)} + m{3/7} n{12/7 + o(1)}) $ which is $ O (n{2 + 2/3}) $ when $ m = \Theta(n2) $. All our algorithms have constant query time in the worst case and are correct with high probability against an oblivious adversary.

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