TY - GEN
T1 - Voronoi-based indoor deployment of mobile sensors network with obstacles
AU - Eledlebi, Khouloud
AU - Ruta, Dymitr
AU - Saffre, Fabrice
AU - Alhammadi, Yousof
AU - Isakovic, Abdel F.
N1 - Funding Information:
ACKNOWLEDGMENT We acknowledgethe support from UAE ICT Fund grant on Biologically Inspired Self-organizingNetwork Services.
Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/2
Y1 - 2019/1/2
N2 - Efficient deployment of wireless sensor network (WSN) is one of the key challenges of the Internet of Things (IoT), and one where self-organizing processes and adaptation to obstacle-rich environments are critical. We developed a Voronoi tessellation based algorithm, BISON (Bio-inspired Self-organized Network), designed to insert and self-deploy nodes of WSN into any unknown, obstacle rich indoor environment, satisfying both, the coverage and the connectivity demands. To limit the power consumption and simulate realistic real-time environment discovery, BISON confines each node to use only locally sensed information, while avoiding obstacles and connecting with neighboring nodes. The algorithm is assessed in terms of the critical deployment evaluation metrics: the area coverage and distance traveled. The results reveal fast convergence to a fully connected network with low deployment costs.
AB - Efficient deployment of wireless sensor network (WSN) is one of the key challenges of the Internet of Things (IoT), and one where self-organizing processes and adaptation to obstacle-rich environments are critical. We developed a Voronoi tessellation based algorithm, BISON (Bio-inspired Self-organized Network), designed to insert and self-deploy nodes of WSN into any unknown, obstacle rich indoor environment, satisfying both, the coverage and the connectivity demands. To limit the power consumption and simulate realistic real-time environment discovery, BISON confines each node to use only locally sensed information, while avoiding obstacles and connecting with neighboring nodes. The algorithm is assessed in terms of the critical deployment evaluation metrics: the area coverage and distance traveled. The results reveal fast convergence to a fully connected network with low deployment costs.
KW - Deployment efficiency
KW - Network connectivity
KW - Network coverage
KW - Self-deployment
KW - Wireless sensors network
UR - https://www.scopus.com/pages/publications/85061555626
U2 - 10.1109/FAS-W.2018.00019
DO - 10.1109/FAS-W.2018.00019
M3 - Conference contribution
AN - SCOPUS:85061555626
T3 - Proceedings - 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018
SP - 20
EP - 21
BT - Proceedings - 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018
Y2 - 3 September 2018 through 7 September 2018
ER -