TY - GEN
T1 - Dynamic gallager-humblet-spira algorithm for wireless sensor networks
AU - Diaz, Sergio
AU - Mendez, Diego
AU - Scholzel, Mario
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/14
Y1 - 2018/9/14
N2 - The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, DGHS finds the minimum spanning tree by executing the GallagerHumblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.
AB - The problem of constructing and maintaining a tree topology in a distributed manner is a challenging task in WSNs. This is because the nodes have limited computational and memory resources and the network changes over time. We propose the Dynamic Gallager-Humblet-Spira (D-GHS) algorithm that builds and maintains a minimum spanning tree. To do so, we divide D-GHS into four phases, namely neighbor discovery, tree construction, data collection, and tree maintenance. In the neighbor discovery phase, the nodes collect information about their neighbors and the link quality. In the tree construction, DGHS finds the minimum spanning tree by executing the GallagerHumblet-Spira algorithm. In the data collection phase, the sink roots the minimum spanning tree at itself, and each node sends data packets. In the tree maintenance phase, the nodes repair the tree when communication failures occur. The emulation results show that D-GHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in memory size and convergence time.
KW - Minimum spanning tree
KW - Tree maintenance
UR - http://www.scopus.com/inward/record.url?scp=85055457102&partnerID=8YFLogxK
U2 - 10.1109/ColComCon.2018.8466704
DO - 10.1109/ColComCon.2018.8466704
M3 - Conference contribution
AN - SCOPUS:85055457102
T3 - 2018 IEEE Colombian Conference on Communications and Computing, COLCOM 2018 - Proceedings
BT - 2018 IEEE Colombian Conference on Communications and Computing, COLCOM 2018 - Proceedings
A2 - Rodriguez, Diana Briceno
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Colombian Conference on Communications and Computing, COLCOM 2018
Y2 - 16 May 2018 through 18 May 2018
ER -