Recent work has pinned down the existentially optimal size bounds for vertex fault-tolerant spanners: for any positive integer k, every n-node graph has a (2k – 1)-spanner on O(f^{1–1/k} n^{1+1/k}) edges resilient to f vertex faults, and there are examples of input graphs on which this bound cannot be improved. However, these proofs work by analyzing the output spanner of a certain exponential-time greedy algorithm. In this work, we give the first algorithm that produces vertex fault tolerant spanners of optimal size and which runs in polynomial time. Specifically, we give a randomized algorithm which takes Õ(f^{1–1/k} n^{2+1/k} + mf2)more »
Local Computation Algorithms for Spanners
A graph spanner is a fundamental graph structure that faithfully preserves the pairwise distances in the input graph up to a small multiplicative stretch. The common objective in the computation of spanners is to achieve the best-known existential size-stretch trade-off efficiently.
Classical models and algorithmic analysis of graph spanners essentially assume that the algorithm can read the input graph, construct the desired spanner, and write the answer to the output tape. However, when considering massive graphs containing millions or even billions of nodes not only the input graph, but also the output spanner might be too large for a single processor to store.
To tackle this challenge, we initiate the study of local computation algorithms (LCAs) for graph spanners in general graphs, where the algorithm should locally decide whether a given edge (u,v)∈E belongs to the output spanner. Such LCAs give the user the `illusion' that a specific sparse spanner for the graph is maintained, without ever fully computing it. We present the following results:
-For general n-vertex graphs and r∈{2,3}, there exists an LCA for (2r−1)-spanners with O˜(n1+1/r) edges and sublinear probe complexity of O˜(n1−1/2r). These size/stretch tradeoffs are best possible (up to polylogarithmic factors).
-For every k≥1 and n-vertex graph with maximum more »
- Publication Date:
- NSF-PAR ID:
- 10108397
- Journal Name:
- Innovations in Theoretical Computer Science (ITCS)
- Sponsoring Org:
- National Science Foundation
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