TY - GEN
T1 - Autonomous deployment of mobile sensors network in an unknown indoor environment with obstacles
AU - Eledlebi, Khouloud
AU - Ruta, Dymitr
AU - Saffre, Fabrice
AU - Al-Hammadi, Yousof
AU - Isakovic, A. F.
N1 - Funding Information:
We gratefully acknowledge the support from UAE ICT Fund grant on “Biologically Inspired Self-organizing Network Services”.
Publisher Copyright:
© 2018 Copyright held by the owner/author(s).
PY - 2018/7/6
Y1 - 2018/7/6
N2 - We developed a Voronoi-based algorithm, called Bio-Inspired Self Organizing Network (BISON), designed to provide a successful deployment of wireless sensor network (WSN) following fast, cost-efficient and self-organizing process, autonomously adapting to the unknown topology of the target environment, and avoiding obstacles discovered in real-time. To limit the power consumed during the deployment, BISON restricts each node to use only locally sensed information to adapt to live-discovered topology while avoiding obstacles and connecting with neighboring nodes. The algorithm is evaluated with respect to several metrics, and simulation results showed faster convergence to a fully connected network with lower deployment costs compared to similar algorithms reported in the literature.
AB - We developed a Voronoi-based algorithm, called Bio-Inspired Self Organizing Network (BISON), designed to provide a successful deployment of wireless sensor network (WSN) following fast, cost-efficient and self-organizing process, autonomously adapting to the unknown topology of the target environment, and avoiding obstacles discovered in real-time. To limit the power consumed during the deployment, BISON restricts each node to use only locally sensed information to adapt to live-discovered topology while avoiding obstacles and connecting with neighboring nodes. The algorithm is evaluated with respect to several metrics, and simulation results showed faster convergence to a fully connected network with lower deployment costs compared to similar algorithms reported in the literature.
UR - http://www.scopus.com/inward/record.url?scp=85051550280&partnerID=8YFLogxK
U2 - 10.1145/3205651.3205725
DO - 10.1145/3205651.3205725
M3 - Conference contribution
AN - SCOPUS:85051550280
T3 - GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
SP - 280
EP - 281
BT - GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
T2 - 2018 Genetic and Evolutionary Computation Conference, GECCO 2018
Y2 - 15 July 2018 through 19 July 2018
ER -