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    Genetic Algorithm Based Energy Efficient Clusters (GABEEC) in Wireless Sensor Networks
    (ELSEVIER SCIENCE BV, 2012) Bayrakli, Selim; Erdogan, Senol Zafer; Shakshuki, E; Younas, M
    In this paper, a genetic algorithm based method (GABEEC) is proposed to optimize the lifetime of wireless sensor networks. The proposed method is a cluster based approach like LEACH. Genetic algorithm is used to maximize the lifetime of the network by means of rounds. The method has 2 phases which are Set-up and Steady-state phase. In the set-up phase, the clusters are created and are not changed throughout the network. The clusters are not recreated for each round. In each round, there are static clusters with dynamically changing clusterheads. A simulator is developed in MS Visual C# 2010 development environment to validate the proposed method. In the simulation, 100 nodes are randomly distributed in 50x50 square meters area. The results show that the proposed method is found to be more efficient than LEACH. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]
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    Internal-genetic-algorithm-based, energy-efficient clusters
    (MAEJO UNIV, 2016) Bayrakli, Selim; Erdogan, Senol Zafer; Kilinc, Turgut
    We propose an internal-genetic-algorithm-based, energy-efficient clustering (INGABEEC) method to enhance the lifetime of wireless sensor networks (WSNs). The proposed method generates energy-efficient clusters by considering several aspects of the WSNs. The INGABEEC generates energy-efficient clusters by genetic algorithm, where cluster heads are changed dynamically. Furthermore, the INGABEEC is improved by using an intra-cluster communication between non-cluster head nodes.