چکیده:
Wireless sensor networks (WSN) are consisted of many sensors which often are located in
harsh and out-of-reach environments. One of the main challenges in WSNs is the limitation
of theenergy consumption. One of applied methods for mitigating the energy consumption
in these WSNs is to make use of the mobile sink in order to collect data of the sensor nodes
from the network. In this research, a new method based on the Genetic Algorithm and fuzzy
logic is proposed for reducing the WSN’s energy consumption using the mobile sink. In
proposed procedure, the suitable mobile sink’s routing is determined using GA. GA
functions based on stop stations position, stop time period and the coverage radius. The
evaluation function in GA calculates the GA responses’ quality with phasing the network’s
residual energy, amount of data collected and balance of energy consumption between
network nodes. The simulation results indicate that the proposed method in different
scenarios provides optimal performance in term of motion rout determination and increase
in WSN lifetime relative to other existing methods.
خلاصه ماشینی:
One of applied methods for mitigating the energy consumption in these WSNs is to make use of the mobile sink in order to collect data of the sensor nodes from the network.
In this research, a new method based on the Genetic Algorithm and fuzzy logic is proposed for reducing the WSN’s energy consumption using the mobile sink.
The simulation results indicate that the proposed method in different scenarios provides optimal performance in term of motion rout determination and increase in WSN lifetime relative to other existing methods.
wireless sensor networks (WSN),energy consumption,mobile sink, genetic algorithm (GA), fuzzy logic Keyword: * Corresponding author: Nazbanuo Farzaneh Bahalgardi Peer review under responsibility of UCT Journal of Research in Science, Engineering and Technology UCT Journal of Research in Science, Engineering and Technology INTRODUCTION Increasingly advances in electronic and telecommunication industries have caused that low energy consuming, smaller size and affordable sensor hardware were designed and developed in different applications.
In this research, criterion function for assessment of chromosomes uses 3 fuzzy parameters: - Network’s residual energy - Amount of data collected by sink - Nodes energy consumption balance Making the network residual energy fuzzy University College of Takestan The fuzzy values for residual energy in network are considered such that previous period energy difference with next period is calculated and the fuzzy values are determined based on the least energy difference.
Fuzzy values are also calculated for energy consumption balance in chromosomes from equation 4 where N is the entire number of network nodes.