Maintaining shortest paths under deletions in weighted directed graphs: [extended abstract]

  • Authors:

  • Aaron Bernstein

  • Affiliations:

  • Columbia University, New York, NY, USA

  • Venue:
  • Proceedings of the forty-fifth annual ACM symposium on Theory of computing
  • Year:
  • 2013

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Abstract

We present an improved algorithm for maintaining all-pairs 1 + ε approximate shortest paths under deletions and weight-increases. The previous state of the art for this problem was total update time ~O (n2√m/ε) for directed, unweighted graphs [2], and ~O(mn/ε) for undirected, unweighted graphs [12]. Both algorithms were randomized and had constant query time. Note that ~O(mn) is a natural barrier because even with a (1 + ε) approximation, there is no o(mn) combinatorial algorithm for the static all-pairs shortest path problem. Our algorithm works on directed, weighted graphs and has total (randomized) update time ~O (mn log(R)/ε) where R is the ratio of the largest edge weight ever seen in the graph, to the smallest such weight (our query time is constant). Note that log(R) = O(log(n)) as long as weights are polynomial in n. Although ~O(mn log(R)/ε) is the total time over all updates, our algorithm also requires a clearly unavoidable constant time per update. Thus, we effectively expand the ~O(mn) total update time bound from undirected, unweighted graphs to directed graphs with polynomial weights. This is in fact the first non-trivial algorithm for decremental all-pairs shortest paths that works on weighted graphs (previous algorithms could only handle small integer weights). By a well known reduction from decremental algorithms to fully dynamic ones [9], our improved decremental algorithm leads to improved query-update tradeoffs for fully dynamic (1 + ε) approximate APSP algorithm in directed graphs.