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    CCHS: AN IMPROVED CENTRALIZED CLUSTER HEAD SELECTION IN WIRELESS SENSOR NETWORKS
    (Journal of Advanced Research in Dynamical and Control Systems, 2019) R, Kowsalya; B, Rosiline Jeetha
    In wireless sensor network, devices or nodes are normally battery powered devices. These nodes have imperfect quantity of primary energy that an enthusiastic at dissimilar rates, depending on the power or energy level. A modified centralized cluster based cluster-head selection is a primary issue in existing representative clustering methods such as M-LEACH and SEDC, cluster heads are selected with a optional likelihood in a distributed manner. So, there are huge deviations of the amount of clusters and size for each cluster at each round throughout network lifetime. In order to conquer issues of difficult cluster-head selection and great energy consumption in Centralized Clustering-Task Scheduling for wireless sensor networks (WSNs), in this paper presents a Modified Centralized Cluster-Head Selection (MCCHS) algorithm based on Simple Energy-efficient Data Collecting (SEDC) protocol was proposed. The proposed system presents a MCCHS algorithm in static manner selection algorithm for cluster head selection technique using NS (Network Simulator) 2.34 Framework. This technique leads to improved CH strength, reduction in the amount of clusters in the network, and improving the energy efficiency.
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    CDARGA: CLUSTER-BASED DATA AGGREGATION WITH GENETIC ROUTING ALGORITHM IN WIRELESS SENSOR NETWORKS
    (International Journal of Recent Technology and Engineering, 2020-02) Kowsalya R; Rosiline Jeetha B
    In the wireless sensor networks (WSNs), the upholding the energy and routing formation at every sensor node is the major issues. The distance from base station and internal node mainly has imbalanced in the energy consumption during transformation of the data. To reduce the energy upholding and the data aggregation routing issues in Centralized Clustering-Task Scheduling for wireless sensor networks (WSNs), this paper focuses on a Cluster-Based Data Aggregation Routing with Genetic search Algorithm (CDARGA) , which reduces the energy consumption in a hyper round model. The proposed data aggregation routing protocol using the Genetic Algorithm (GA) estimates the fitness function using the three key parameters distance, energy, and Hyper round policy. The proposed methods were compared with RP-MAC and the experimental result shows that the proposed protocol is superior to RP-MAC protocol and the proposed algorithm improves the network lifetime which can used in real time application.