Grey Wolves Optimizer-based Localization Approach in WSNs

Citation:
Fouad, M. M., A. I. Hafez, A. E. Hassanien, and V. Snasel, "Grey Wolves Optimizer-based Localization Approach in WSNs", IEEE iInternational Computer Engineering Conference - ICENCO , Bilbao, Spain, 30 Dec, 2015.

Date Presented:

30 Dec

Abstract—Localization is one of the main challenge in wireless
sensor networks (WSNs). Since both routing establishment and
coverage performance of a sensor network are directly affected
by the nodes’ localizations. While knowing the position of
each node is important, a small number of researches had
considered the importance of the localization of the sink node.
Therefore this paper presents a sink node localization approach
based on Grey Wolves Optimizer (GWO). The approach was
evaluated against the performance of specific protocols of WSNs
(Topology Control Protocols). Through a number of simulation
experiments for a different sized nodes’ deployment scenarios, it
became obviously that the proposed approach had minimized the
average of each of energy cost and the number of active nodes
along with the time required to construct a reduced topology.