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  • Küçük Resim
    Öğe
    2D coverage analysis of sensor networks with random node deployment
    (IEEE, 2017) Birtane, Sibel; Kazdal, Seda; Şahingöz, Özgür Koray
    In last few decades, as a result of the advances in microelectromechanical systems, Wireless Sensor Networks (WSNs) have gained a considerable attention due to their low-cost, low-power and small-scale sensor nodes which are used to integrate sensing, processing, communicating capabilities to solve many different real world problems. The placement of sensor nodes is a very important step to cover the theater of these application areas. Increasing the coverage of WSN system is one of the important research interests to determine the quality of service of the system. The location of sensor nodes can be determined by humans to increase the coverage area. However, in the remote or hostile environments, the random deployment of sensor nodes is needed to be used. In this paper, the different random deployment techniques have been studied, and the experimental results are obtained have been shared to show the effectiveness of these techniques. Finally, the alternative approaches are mentioned to guide the researchers, as well.
  • Küçük Resim
    Öğe
    A multi agent solution for UAV path planning problem with NetLogo
    (Research India Publications, 2016) Kazdal Çalık, Seda; Kuğu, Emin; Birtane, Sibel; Şahingöz, Özgür Koray
    Due to its low cost, small size, autonomous structure and high mobility, usage of the Unmanned Aerial Vehicles (UAVs) has been increasing over the last two decades. To construct an autonomous UAV, path planning is a crucial task to meet the objectives specified for the mission. Mainly, the purpose of path planning can be described as find the optimal path from a start point to the destination point to check necessary control points (CPs) while taking into consideration different operational constraints. While the number of CPs increases, constructing an optimal path is getting trivial, most of the researchers used evolutionary algorithms and/or swarm algorithms to reach a near optimal solution in an acceptable time. In this study, it is aimed to solve the UAV Path Planning problem with a swarm intelligence algorithm as Ant Colony Optimization Algorithm. To implement this algorithm with similar to the real world, each ant is aimed to implement as an autonomous agent, and the proposed system is implemented on NetLogo, which is a multi-agent programmable modeling environment for simulating real World problems. The experimental results showed that the proposed system produces an acceptable solution in a limited time.