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On the complexity of the shortest-path broadcast problem

Authors: CRESCENZI, PIERLUIGI; Fraigniaud, Pierre; Halldórsson, Magnus; Harutyunyan, Hovhannes A.; Pierucci, Chiara; Pietracaprina, Andrea; Pucci, Geppino;

On the complexity of the shortest-path broadcast problem

Abstract

We study the shortest-path broadcast problem in graphs and digraphs, where a message has to be transmitted from a source node s to all the nodes along shortest paths, in the classical telephone model. For both graphs and digraphs, we show that the problem is equivalent to the broadcast problem in layered directed graphs. We then prove that this latter problem is NP-hard, and therefore that the shortest-path broadcast problem is NP-hard in graphs as well as in digraphs. Nevertheless, we prove that a simple polynomial-time algorithm, called MDST-broadcast, based on min-degree spanning trees, approximates the optimal broadcast time within a multiplicative factor? 3 2 in 3-layer digraphs, and O ( log n log log n ) in arbitrary multi-layer digraphs. As a consequence, one can approximate the optimal shortest-path broadcast time in polynomial time within a multiplicative factor? 3 2 whenever the source has eccentricity at most?2, and within a multiplicative factor? O ( log n log log n ) in the general case, for both graphs and digraphs. The analysis of MDST-broadcast is tight, as we prove that this algorithm cannot approximate the optimal broadcast time within a factor smaller than ? ( log n log log n ) .

Countries
France, Italy, France
Keywords

Broadcast time; Communication networks; Layered graphs; Shortest paths, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Average
Green
hybrid