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  • Asynchronous Optimization Algorithms for the Enhancement of Lifetime in WSNs
    Abdullah Alshahrani1, M. Namazi1, Majed Abdouli2, 1Department of Electrical Engineering and Computer Science,The Catholic University of America, 2Department of and Computer Science, University of Jedda

    Efficient utilization of sensor energy to prolong the network lifetime has been the focus of much research on WSNs. In order to save the overall energy of the system and to balance the load among sensors nodes we proposes a hybrid PSO Genetic scheduling algorithm for WSNs to escape the local optima trap. The latter can appear when running PSO. In fact, this asynchronous scheme uses a new parameter: Local Optimum Detector (LOD) for switching from PSO to GA algorithm. In addition, clustering routing protocol is needed to reduce the communication cost and evaluate the network lifetime. In this paper, Fuzzy C-Means (FCM) makes the clustering algorithm in our work. In this paper, we show how these solutions sums up the benefits of two techniques: clustering and sleep scheduling asynchronous optimization algorithms that will advance environment monitoring applications and allows the WSN to survive as long as possible.

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