2009 | OriginalPaper | Buchkapitel
Incompressibility through Colors and IDs
verfasst von : Michael Dom, Daniel Lokshtanov, Saket Saurabh
Erschienen in: Automata, Languages and Programming
Verlag: Springer Berlin Heidelberg
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In parameterized complexity each problem instance comes with a parameter
k
, and a parameterized problem is said to admit a
polynomial kernel
if there are polynomial time preprocessing rules that reduce the input instance to an instance with size polynomial in
k
. Many problems have been shown to admit polynomial kernels, but it is only recently that a framework for showing the non-existence of polynomial kernels has been developed by Bodlaender et al. [4] and Fortnow and Santhanam [9]. In this paper we show how to combine these results with combinatorial reductions which use colors and IDs in order to prove kernelization lower bounds for a variety of basic problems:
We show that the
Steiner Tree
problem parameterized by the number of terminals and solution size
k
, and the
Connected Vertex Cover
and
Capacitated Vertex Cover
problems do not admit a polynomial kernel. The two latter results are surprising because the closely related
Vertex Cover
problem admits a kernel of size 2
k
.
Alon and Gutner obtain a
k
poly
(
h
)
kernel for
Dominating Set in
H
-Minor Free Graphs
parameterized by
h
= |
H
| and solution size
k
and ask whether kernels of smaller size exist [2]. We partially resolve this question by showing that
Dominating Set in
H
-Minor Free Graphs
does not admit a kernel with size polynomial in
k
+
h
.
Harnik and Naor obtain a “compression algorithm” for the
Sparse Subset Sum
problem [13]. We show that their algorithm is essentially optimal since the instances cannot be compressed further.
Hitting Set
and
Set Cover
admit a kernel of size
k
O
(
d
)
when parameterized by solution size
k
and maximum set size
d
. We show that neither of them, along with the
Unique Coverage
and
Bounded Rank Disjoint Sets
problems, admits a polynomial kernel.
All results are under the assumption that the polynomial hierarchy does not collapse to the third level. The existence of polynomial kernels for several of the problems mentioned above were open problems explicitly stated in the literature [2,3,11,12,14]. Many of our results also rule out the existence of compression algorithms, a notion similar to kernelization defined by Harnik and Naor [13], for the problems in question.