Перегляд за Автор "Sushyn, Ihor O."

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    Development of methods of positioning, localization and data collection from nodes of a free mobile sensor network using intelligent adaptive telecommunication aeroplatforms
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2021) Romaniuk, Valery A.; Lysenko, Olexandr I.; Novikov, Valery I.; Sushyn, Ihor O.
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    Evaluating the functioning effectiveness of sensor ground-to-air network using multiple UAVS layers and directional antennas
    (National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2024) Sushyn, Ihor O.; Ivashchev, Daniil V.; Lysenko, Olexandr I.
    Background. Based on the theoretical and practical (using Atoll) calculation of radio communication lines and antenna devices were estimated the main network parameters (throughput, length of the data transmission route, delays, number of network elements) of proposed ground to air network (GAN) architecture. Objective. The purpose of the work is to evaluate the effectiveness of mobile networks with directed action sensors using UAVs at different levels. Methods. Simulation modelling of two mathematical models and their comparison using MATLAB software. Results. It is shown that the throughput decreases with the increase of the data transmission route, while the delay and the number of network elements increase in accordance with the previous study. Changing the location of the nodes also affects the parameters evaluated, so 10,000 measurements were made to obtain the required amount of statistical data. Two mathematical models were created. The first model is based on an existing mobile omnidirectional sensor network using a single UAV layer while the second one is based on a mobile network of directional sensors using two levels of UAVs. In both models, the data was transmitted from the nodes to the pseudo-satellite. In the proposed model, the following average values were achieved: throughput - 852071 bits/s, number of network elements - 4.4, route length - 33673 meters. Conclusions. According to the obtained results, it can be argued that the proposed two-level UAV location model using directional sensors can be effectively used to maintain the connectivity of a mobile sensor network with the achievement of a gain in the evaluated indicators.
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    The program for assessing the connectivity of nodes of wireless episodic networks under the condition of using UAVS
    (National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2023) Sushyn, Ihor O.; Lysenko, Olexandr I.; Valuiskyi, Stanislav V.
    Background. Based on analytical mathematical models, the duration of connectivity of mobile subscribers (nodes) (MS) of a wireless episodic network (WEN, consisting of MS and UAV) was investigated in conditions of direct radio visibility and considering the relaying. Objective. The purpose of the work is to find methodological approaches to ensure the connectivity of WSN nodes, which is a necessary condition for obtaining information from WSN in the absence of communication infrastructure. Methods. Simulation modelling based on MAPLE 14 software package and analytical calculation methods are used. Results. It is shown that the duration of connectivity is directly proportional to the size of the coverage area and inversely proportional to the movement speed of nodes. The mobility nature (scenario) of nodes also affects the duration of connectivity. The simulation of the nodes' movement was carried out under 4 scenarios: "march", "incoherent", "random wandering in the field" and "random wandering in the city". The largest values of the connectivity duration correspond to the third scenario, and the smallest - to the second (with a fixed radius of the coverage area and the movement speed of nodes). Thus, the average connectivity duration of the UAV-pedestrian connection in the event of an "incoherent" will be about 36 minutes, and the UAV-car connection - about 5 minutes. Conclusions. The system and functional parameters of the networks, which were obtained as a result of the research, will form the basis of the initial data and limitations of the mathematical model, and will also make it possible to determine the initial placement of the UAV network at the planning stage.