Fast distributed algorithm for convergecast in ad hoc geometric radio networks

Alex Kesselman, Dariusz R. Kowalski

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Wireless ad hoc radio networks have gained a lot of attention in recent years. We consider geometric networks, where nodes are located in a Euclidean plane. We assume that each node has a variable transmission range and can learn the distance to the closest active neighbor at any time. We also assume that nodes have a special collision detection (CD) capability so that a transmitting node can detect a collision within its transmission range. We study the basic communication problem of collecting data from all nodes called convergecast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent delay requirements on the convergecast time. We measure the latency of convergecast, that is the number of time steps needed to collect the data in any n-node network. We propose a very simple randomized distributed algorithm that has the expected running time O(logn). We also show that this bound is tight and any algorithm needs Ω(logn) time steps while performing convergecast in an arbitrary network. One of the most important problems in wireless ad hoc networks is to minimize the energy consumption, which maximizes the network lifetime. We study the trade-off between the energy and the latency of convergecast. We show that our algorithm consumes at most O(nlogn) times the minimum energy. We also demonstrate that for a line topology, the minimum energy convergecast takes n time steps while any algorithm performing convergecast within O(logn) time steps requires Ω(n/logn) times the minimum energy.

Original languageEnglish (US)
Pages (from-to)578-585
Number of pages8
JournalJournal of Parallel and Distributed Computing
Issue number4
StatePublished - Apr 2006
Externally publishedYes


  • Convergecast
  • Energy/latency trade-off
  • Radio networks
  • Randomized algorithms

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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