IMPROVING COVERAGE IN WIRELESS SENSOR NETWORKS USING MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS


YILDIRIM OKAY F., Ozdemir S.

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.30, sa.2, ss.143-153, 2015 (SCI-Expanded) identifier identifier

Özet

Node deployment is one of the important issues to be addressed in Wireless Sensor Networks (WSNs). A proper node deployment scheme can reduce the complexity of problems in WSNs such as routing, data fusion, communication, etc. Sensors in Mobile WSNs (MWSNs) have ability to travel in the network with motion capability. This ability can extend the lifetime of WSNs by minimizing energy consumption due to travelling with optimization of deployment. This paper employs two recently proposed multi-objective optimization algorithms, namely multi-objective evolutionary algorithm based on decomposition (MOEA/D) and fast and elitist genetic algorithm (NSGA-II) to find proper deployment scenarios. These multi-objective evolutionary algorithms aim at relocating mobile nodes to provide maximum sensing coverage area while minimizing the energy required for the relocation. The relocation is defined as the total travel distance of the sensors from their initial locations to their final locations. Simulation results clearly show that the non-dominated solutions have tradeoff between the travelled distance and coverage area.