Yazar "Al Hayali, Shaymaa" seçeneğine göre listele

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    Detection of attacks on wireless sensor network using genetic algorithms based on fuzzy
    (Diponegoro Univ, 2019) Al Hayali, Shaymaa; Uçan, Osman Nuri; Rahebi, Javad; Bayat, Oğuz
    In this paper an individual - suitable function calculating design for WSNs is conferred. A multi-agent-located construction for WSNs is planned and an analytical type of the active combination is built for the function appropriation difficulty. The purpose of this study is to identify the threats identified by clustering genetic algorithms in clustering networks, which will prolong network lifetime. In addition, optimal routing is done using the fuzzy function. Simulation results show that the simulated genetic algorithm improves diagnostic speed and improves energy consumption. (c) 2019. CBIORE-IJRED. All rights reserved
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    Öğe
    Increasing energy efficiency in wireless sensor networks using GA-ANFIS to choose a cluster head and Assess Routing and Weighted Trusts to demodulate attacker nodes
    (Springer, 2020) Al Hayali, Shaymaa; Rahebi, Javad; Uçan, Osman Nuri; Bayat, Oğuz
    Demodulating harmful nodes and diminishing the energy waste in sensor nodes can prolong the lifespan of wireless sensor networks (WSNs). In this study, a genetic algorithm (GA) and an adaptive neuro fuzzy inference system were used to diminish the energy waste of sensors. Weighted trust evaluation was applied to search for harmful nodes in the network to prolong the lifespan of WSNs. A low-energy adaptive clustering hierarchy method was used to analyze the results. It was discovered that searching for harmful nodes with GA-ANFIS using weighted trust evaluation significantly increased the lifespan of WSNs. For evaluation of the proposed method we used the mean of energy of all sensors against of the round, data packets received in base station, minimum energy versus rounds and number of alive sensors versus rounds. Also, in this paper we compared the proposed method results with LEACH, LEACH-DT, Random, SIF and GA-Fuzzy methods. As results the proposed method has high life time than other methods. A representation of the overall system was implemented using MATLAB software.