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  • Open Access


    Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

    A. Jameer Basha1, S. Aswini1, S. Aarthini1, Yunyoung Nam2,*, Mohamed Abouhawwash3,4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1451-1466, 2023, DOI:10.32604/csse.2023.025503

    Abstract Wireless Sensor Network (WSN) technology is the real-time application that is growing rapidly as the result of smart environments. Battery power is one of the most significant resources in WSN. For enhancing a power factor, the clustering techniques are used. During the forward of data in WSN, more power is consumed. In the existing system, it works with Load Balanced Clustering Method (LBCM) and provides the lifespan of the network with scalability and reliability. In the existing system, it does not deal with end-to-end delay and delivery of packets. For overcoming these issues in WSN, the proposed Genetic Algorithm based… More >

  • Open Access


    Improved Load-Balanced Clustering for Energy-Aware Routing (ILBC-EAR) in WSNs

    D. Loganathan1,*, M. Balasubramani1, R. Sabitha2, S. Karthik2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 99-112, 2023, DOI:10.32604/csse.2023.023120

    Abstract Sensors are considered as important elements of electronic devices. In many applications and service, Wireless Sensor Networks (WSNs) are involved in significant data sharing that are delivered to the sink node in energy efficient manner using multi-hop communications. But, the major challenge in WSN is the nodes are having limited battery resources, it is important to monitor the consumption rate of energy is very much needed. However, reducing energy consumption can increase the network lifetime in effective manner. For that, clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes. In that concern, this… More >

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