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Sublinear-Time Decremental Algorithms for Single-Source Reachability and Shortest Paths on Directed Graphs

Published 29 Apr 2015 in cs.DS | (1504.07959v2)

Abstract: We consider dynamic algorithms for maintaining Single-Source Reachability (SSR) and approximate Single-Source Shortest Paths (SSSP) on nn-node mm-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) O(1) query time and O(mn) 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<sup>7/6</sup>n<sup>2/3</sup>+o(1),m<sup>3/4</sup>n<sup>5/4</sup>+o(1)))=O(mn<sup>9/10</sup>+o(1)) O(\min (m<sup>{7/6}</sup> n<sup>{2/3</sup> + o(1)}, m<sup>{3/4}</sup> n<sup>{5/4</sup> + o(1)}) ) = O (m n<sup>{9/10</sup> + o(1)}) for SSR and (1+ϵ)(1+\epsilon)-approximate SSSP if the edge weights are integers from $ 1 $ to W2<sup>log<sup>cn</sup></sup> W \leq 2<sup>{\log<sup>c{n}}</sup></sup> and ϵ1/log<sup>cn</sup> \epsilon \geq 1 / \log<sup>c{n}</sup> for some constant c 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=Θ(n) m = \Theta(n) its running time is O(n<sup>1</sup>+5/6+o(1)) O (n<sup>{1</sup> + 5/6 + o(1)}) and when m=Θ(n<sup>2)</sup> m = \Theta(n<sup>2)</sup> its running time is O(n<sup>2</sup>+3/4+o(1)) O (n<sup>{2</sup> + 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<sup>2/3</sup>n<sup>4/3</sup>+o(1)+m<sup>3/7</sup>n<sup>12/7</sup>+o(1)) O ( m<sup>{2/3}</sup> n<sup>{4/3</sup> + o(1)} + m<sup>{3/7}</sup> n<sup>{12/7</sup> + o(1)}) which is O(n<sup>2</sup>+2/3) O (n<sup>{2</sup> + 2/3}) when m=Θ(n<sup>2)</sup> m = \Theta(n<sup>2)</sup> . 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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