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Information gathering in ad-hoc radio networks with tree topology

  • Marek Chrobak(corresponding author)
    ,
  • Kevin Costello
    ,
  • Leszek Gasieniec
    ,
*Corresponding author for this work
  • University of California at Riverside
    ,
  • University of Liverpool
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

We study information gathering in ad-hoc radio networks without collision detection, focussing on the case when the network forms a tree with edges directed towards the root. Initially, each node has a piece of information that we refer to as a rumor. The goal is to deliver all rumors to the root of the tree as quickly as possible. The protocol must complete this task even if the tree topology is unknown. In the deterministic case, assuming that the nodes are labeled with small integers, we give an O(n)-time protocol that uses unbounded messages, and an O(n log n)-time protocol using bounded messages. We also consider fireand- forward protocols, in which a node can only transmit its own rumor or the rumor received in the previous step. We give a deterministic fire-and-forward protocol with running time O(n1.5), and we show that it is asymptotically optimal. We then study randomized algorithms where the nodes are not labelled. In this model, we give an O(n log n)-time protocol and we prove that this bound is asymptotically optimal.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 129-145 (17 pages)

Journal (Volume, Issue Number)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Volume 8881)

Publication milestones

  • Published - 2014

Publication status

Published - 2014

ISSN

0302-9743

Publication IDs

  • Scopus: 84921489746

Publication metrics

Metrics

Scopus
citations
Fractional count
2
Fractional count
0.50
Fractional count
2
Fractional count
0.50
Fractional count
2
Fractional count
1
SciVal
FWCI
0.23
SciVal
Author count
4
SciVal
citations
2
SciVal
Paper percentile
41

PlumX, opens in new tab

Captures
4
Citation count
2

Funding Details

Research supported by grants CCF-1217314 (NSF) and H98230-13-1-0228 (NSA).
FundersFunding numbers
NSA
-
NSF
CCF-1217314
NSF
1217314, 1157129, H98230-13-1-0228