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A large number of streaming papers consider graph problems. Typically, the input stream is an arbitrarily-ordered sequence of edges. For many problems, one can show that solving the problem, even approximately, requires \Omega(n) bits of space. | A large number of streaming papers consider graph problems. Typically, the input stream is an arbitrarily-ordered sequence of edges. For many problems, one can show that solving the problem, even approximately, requires \Omega(n) bits of space. |
Revision as of 05:24, 16 November 2012
Suggested by | Krzysztof Onak |
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Source | Kanpur 2009 |
Short link | https://sublinear.info/29 |
A large number of streaming papers consider graph problems. Typically, the input stream is an arbitrarily-ordered sequence of edges. For many problems, one can show that solving the problem, even approximately, requires \Omega(n) bits of space. For instance, one can relatively easily prove that finding a constant-factor approximation to the maximum matching problem requires \Omega(n) bits of space. Therefore, in many cases, the desired space complexity is of the form \tilde O(n). Despite this relaxation, it is plausible that for some popular problems, there are barriers that cannot be overcome by (approximate) algorithms that use n^{1+o(1)} space and a small number of passes.
For example, let M(G) be the maximum matching size in the input graph G. McGregor [McGregor-05] shows that there is an algorithm that finds a matching of size (1-\epsilon) \cdot M(G) in a number of passes that is a function of only \epsilon. It is plausible that for any constant k, there is no k-pass \tilde O(n)-space algorithm that finds a matching of size greater than (1-\epsilon_k) \cdot M(G) times the optimum, where \epsilon_k is a positive constant. In particular, to the best of my knowledge, no one-pass \tilde O(n)-space algorithm that finds a (1-\epsilon)-approximation for any constant \epsilon \in (0,1/2) is known. Can one prove lower bounds as suggested above? The question generalizes to other problems. For instance, the best known \tilde O(n)-space algorithms for simulating random walks require a large number of passes (see [DasSarmaGP-08] and Rina Panigrahy's question). Can one prove for these problems that a small number of passes requires n^{1+\Omega(1)} space?
To the best of my knowledge, the only problem for which this kind of lower bound is known is approximating graph distances. Feigenbaum et al. [FeigenbaumKMSZ-08] show that obtaining a t-approximation for the distance between two nodes in a single pass requires \Omega(n^{1+1/t}) space.