Semi-Streaming Matching in a Single Pass II: Greedy is Optimal
- View PDF HTML (experimental) Abstract:We prove that no single-pass semi-streaming algorithm (deterministic or randomized) can achieve a better-than-half approximation to the maximum matching problem.
- This implies the optimality of the naive greedy algorithm, answering an outstanding open question in the graph streaming literature since the introduction of the model over two decades ago.
- Our proof follows the "blueprint framework" introduced previously by the authors, which reduced proving lower bounds for semi-streaming matching to constructing certain combinatorial objects called blueprints.
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- View PDF HTML (experimental) Abstract:We prove that no single-pass semi-streaming algorithm (deterministic or randomized) can achieve a better-than-half approximation to the maximum matching problem.
- This implies the optimality of the naive greedy algorithm, answering an outstanding open question in the graph streaming literature since the introduction of the model over two decades ago.
- Our proof follows the "blueprint framework" introduced previously by the authors, which reduced proving lower bounds for semi-streaming matching to constructing certain combinatorial objects called blueprints.
Sources: Arxiv