TY - JOUR
T1 - SmartBone
T2 - An energy-efficient smart backbone construction in wireless sensor networks
AU - Chuang, Shun Yu
AU - Chen, Chien
PY - 2007/7/1
Y1 - 2007/7/1
N2 - Wireless sensor network is a rapidly growing discipline with new technologies emerging, and new applications under development. The nodes in a wireless network generally communicate with each other along the same wireless channel. Unfortunately, sharing among wireless channels decreases network performance due to radio interference, and also raises energy consumption due to packet retransmission when interference occurs. Many topology control algorithms have been proposed to solve these problems. One widely used strategy is the backbone method. Backbone algorithms aim to reduce the backbone size. However, poor performance may be explored if only few backbone nodes are selected. Therefore, several heuristic algorithms such as SBC have been proposed. However, these algorithms cannot efficiently eliminate redundant nodes, and dramatically decrease performance, especially in relatively sparse networks. This study proposes a novel heuristic-based backbone algorithm called SmartBone to choose proper backbone nodes from a network. SmartBone includes two major mechanisms. FlowBottleneck preprocessing is adopted to find critical nodes, which act as backbone nodes to improve connectivity. Dynamic Density Cutback is adopted to reduce the number of redundant nodes depending on local area node density of network. SmartBone simultaneously considers the balance of network performance and energy savings. Significantly, the proposed algorithm has a 50% smaller backbone size than SBC, and improves the energy saving ratio from 25% using SBC to 40% using SmartBone. Moreover, SmartBone improves the packet delivery ratio from 40% to 90% when the density of sensor networks becomes relatively sparser.
AB - Wireless sensor network is a rapidly growing discipline with new technologies emerging, and new applications under development. The nodes in a wireless network generally communicate with each other along the same wireless channel. Unfortunately, sharing among wireless channels decreases network performance due to radio interference, and also raises energy consumption due to packet retransmission when interference occurs. Many topology control algorithms have been proposed to solve these problems. One widely used strategy is the backbone method. Backbone algorithms aim to reduce the backbone size. However, poor performance may be explored if only few backbone nodes are selected. Therefore, several heuristic algorithms such as SBC have been proposed. However, these algorithms cannot efficiently eliminate redundant nodes, and dramatically decrease performance, especially in relatively sparse networks. This study proposes a novel heuristic-based backbone algorithm called SmartBone to choose proper backbone nodes from a network. SmartBone includes two major mechanisms. FlowBottleneck preprocessing is adopted to find critical nodes, which act as backbone nodes to improve connectivity. Dynamic Density Cutback is adopted to reduce the number of redundant nodes depending on local area node density of network. SmartBone simultaneously considers the balance of network performance and energy savings. Significantly, the proposed algorithm has a 50% smaller backbone size than SBC, and improves the energy saving ratio from 25% using SBC to 40% using SmartBone. Moreover, SmartBone improves the packet delivery ratio from 40% to 90% when the density of sensor networks becomes relatively sparser.
KW - Backbone
KW - Critical nodes
KW - Density cutback
KW - Distributed DFS
KW - Energy saving
KW - Flow-bottleneck preprocessing
KW - Topology control
UR - http://www.scopus.com/inward/record.url?scp=34547398896&partnerID=8YFLogxK
U2 - 10.6688/JISE.2007.23.4.5
DO - 10.6688/JISE.2007.23.4.5
M3 - Article
AN - SCOPUS:34547398896
VL - 23
SP - 1023
EP - 1039
JO - Journal of Information Science and Engineering
JF - Journal of Information Science and Engineering
SN - 1016-2364
IS - 4
ER -