Abstract
We consider the question of how much information can be stored by labeling the vertices of a connected undirected graph G using a constant-size set of labels, when isomorphic labelings are not distinguishable. Specifically, we are interested in the effective capacity of members of some class of graphs, the number of states distinguishable by a Turing machine that uses the labeled graph itself in place of the usual linear tape. We show that the effective capacity is related to the information-theoretic capacity which we introduce in the paper. It equals the information-theoretic capacity of the graph up to constant factors for trees, random graphs with polynomial edge probabilities, and bounded-degree graphs.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 44-56 |
| Number of pages | 13 |
| Journal | Information and Computation |
| Volume | 234 |
| DOIs | |
| State | Published - Feb 2014 |
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ASJC Scopus subject areas
- Information Systems
- Computational Theory and Mathematics
- Theoretical Computer Science
- Computer Science Applications
Cite this
Effective storage capacity of labeled graphs. / Angluin, Dana; Aspnes, James; Bazzi, Rida; Chen, Jiang; Eisenstat, David; Konjevod, Goran.
In: Information and Computation, Vol. 234, 02.2014, p. 44-56.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Effective storage capacity of labeled graphs
AU - Angluin, Dana
AU - Aspnes, James
AU - Bazzi, Rida
AU - Chen, Jiang
AU - Eisenstat, David
AU - Konjevod, Goran
PY - 2014/2
Y1 - 2014/2
N2 - We consider the question of how much information can be stored by labeling the vertices of a connected undirected graph G using a constant-size set of labels, when isomorphic labelings are not distinguishable. Specifically, we are interested in the effective capacity of members of some class of graphs, the number of states distinguishable by a Turing machine that uses the labeled graph itself in place of the usual linear tape. We show that the effective capacity is related to the information-theoretic capacity which we introduce in the paper. It equals the information-theoretic capacity of the graph up to constant factors for trees, random graphs with polynomial edge probabilities, and bounded-degree graphs.
AB - We consider the question of how much information can be stored by labeling the vertices of a connected undirected graph G using a constant-size set of labels, when isomorphic labelings are not distinguishable. Specifically, we are interested in the effective capacity of members of some class of graphs, the number of states distinguishable by a Turing machine that uses the labeled graph itself in place of the usual linear tape. We show that the effective capacity is related to the information-theoretic capacity which we introduce in the paper. It equals the information-theoretic capacity of the graph up to constant factors for trees, random graphs with polynomial edge probabilities, and bounded-degree graphs.
UR - http://www.scopus.com/inward/record.url?scp=84894268389&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894268389&partnerID=8YFLogxK
U2 - 10.1016/j.ic.2013.11.004
DO - 10.1016/j.ic.2013.11.004
M3 - Article
VL - 234
SP - 44
EP - 56
JO - Information and Computation
JF - Information and Computation
SN - 0890-5401
ER -