Fast distributed algorithm for convergecast in ad hoc geometric radio networks

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 assum...

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Bibliographic Details
Published in:Journal of parallel and distributed computing Vol. 66; no. 4; pp. 578 - 585
Main Authors: Kesselman, Alex, Kowalski, Dariusz R.
Format: Journal Article
Language:English
Published: Elsevier Inc 01.04.2006
Subjects:
Convergecast
Energy/latency trade-off
Radio networks
Randomized algorithms
Convergecast
Randomized algorithms
Radio networks
Energy/latency trade-off
ISSN:0743-7315, 1096-0848
Online Access:Get full text
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Summary: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 ( log n ) . We also show that this bound is tight and any algorithm needs Ω ( log n ) 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 ( n log n ) 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 ( log n ) time steps requires Ω ( n / log n ) times the minimum energy.
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2005.11.004