Sensor networks have promising applications such as battlefield surveillance, biological detection, and emergency navigation, etc. Crucial problems in sensor networks are energy-efficiency and collision avoidance in wireless communication. To deal with the problems, we consider a self-stabilizing solution to the construction of k disjoint sense-sleep trees, where range adjustment and the use of GPS are allowed. Each root is determined by its identifier and is distinguished by its color, the identification of a tree. Using a dominating k-partition rule, each non-root node first determines a color irrelevant to the root. Then, the non-root node determines a parent node that is equally colored with minimal distance. If there is no appropriate parent, the range is extended or shrunk until the nearest parent is determined. Finally, we perform a simulation.
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Jun KINIWA, "Construction of Self-Stabilizing k Disjoint Sense-Sleep Trees with Application to Sensor Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 4, pp. 1174-1181, April 2009, doi: 10.1587/transfun.E92.A.1174.
Abstract: Sensor networks have promising applications such as battlefield surveillance, biological detection, and emergency navigation, etc. Crucial problems in sensor networks are energy-efficiency and collision avoidance in wireless communication. To deal with the problems, we consider a self-stabilizing solution to the construction of k disjoint sense-sleep trees, where range adjustment and the use of GPS are allowed. Each root is determined by its identifier and is distinguished by its color, the identification of a tree. Using a dominating k-partition rule, each non-root node first determines a color irrelevant to the root. Then, the non-root node determines a parent node that is equally colored with minimal distance. If there is no appropriate parent, the range is extended or shrunk until the nearest parent is determined. Finally, we perform a simulation.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1174/_p
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@ARTICLE{e92-a_4_1174,
author={Jun KINIWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Construction of Self-Stabilizing k Disjoint Sense-Sleep Trees with Application to Sensor Networks},
year={2009},
volume={E92-A},
number={4},
pages={1174-1181},
abstract={Sensor networks have promising applications such as battlefield surveillance, biological detection, and emergency navigation, etc. Crucial problems in sensor networks are energy-efficiency and collision avoidance in wireless communication. To deal with the problems, we consider a self-stabilizing solution to the construction of k disjoint sense-sleep trees, where range adjustment and the use of GPS are allowed. Each root is determined by its identifier and is distinguished by its color, the identification of a tree. Using a dominating k-partition rule, each non-root node first determines a color irrelevant to the root. Then, the non-root node determines a parent node that is equally colored with minimal distance. If there is no appropriate parent, the range is extended or shrunk until the nearest parent is determined. Finally, we perform a simulation.},
keywords={},
doi={10.1587/transfun.E92.A.1174},
ISSN={1745-1337},
month={April},}
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TY - JOUR
TI - Construction of Self-Stabilizing k Disjoint Sense-Sleep Trees with Application to Sensor Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1174
EP - 1181
AU - Jun KINIWA
PY - 2009
DO - 10.1587/transfun.E92.A.1174
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2009
AB - Sensor networks have promising applications such as battlefield surveillance, biological detection, and emergency navigation, etc. Crucial problems in sensor networks are energy-efficiency and collision avoidance in wireless communication. To deal with the problems, we consider a self-stabilizing solution to the construction of k disjoint sense-sleep trees, where range adjustment and the use of GPS are allowed. Each root is determined by its identifier and is distinguished by its color, the identification of a tree. Using a dominating k-partition rule, each non-root node first determines a color irrelevant to the root. Then, the non-root node determines a parent node that is equally colored with minimal distance. If there is no appropriate parent, the range is extended or shrunk until the nearest parent is determined. Finally, we perform a simulation.
ER -