Sensor deployment for fault diagnosis using a new discrete optimization algorithm

Authors:
Javad Alikhani Koupaei;Marjan Abdechiri
Affiliations:
Department of Mathematics, Payame Noor University, PO Box 19395-3697, Tehran, Iran;Young Researchers Club, Mobarakeh Branch, Islamic Azad University, Isfahan, Iran
Venue:
Applied Soft Computing
Year:
2013

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Abstract

Optimal allocation of the sensor in a wireless sensor network (WSN) is required to have a satisfactory fault diagnosis within the system. In fact, the sensor nodes in the network should be located in an arrangement to maximize the failure diagnosis. In this paper, the sensor deployment optimization to diagnose the distributed failures in a wireless unmanned aerial vehicles (UAVs) network has been studied. In this way, a novel evolutionary optimization algorithm inspired by the gases Brownian and turbulent rotational motion is utilized which is called Discrete Gases Brownian Motion Optimization (DGBMO) algorithm. An integer linear programming (ILP) approach is used to formulate the sensor deployment. Then the sensor deployment optimization is solved by DGBMO as well as generic ILP solvers and Boolean satisfiability-based ILP solvers. The results show that DGBMO is suitable for sensor disposition optimization especially in large-sized UAV networks.