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• W4243112836 abstract "The cluster formation using swarm intelligence techniques are performed with better optimization. Conventional optimization algorithm increases the processing stage and it performed with in the space, which is allocated from user. Therefore, the proposed work is utilized to design with better performance results. In this paper, we propose an optimal cluster-based multiple sink reconnection technology for wireless sensor networks using a hybrid optimization algorithm. The proposed design used an intermediate sensor/mobile node next to the sink node and a sensor node ready to transmit data. Here, the weighted k-mean algorithm is converted to a cluster node. The optimal cluster head code was chosen using a mass optimization method that targets the available energy and available bandwidth for successfully transferring data without node optimization. So with resource updates, you can find the right location for your sink node for better data transfer. This assists with tracking down the most appropriate situation for the sink hub where it very well may be situated to guarantee better information transmission with asset advancement. Overall, the comparison shows the better performance analysis of various optimization is done successfully." @default.
• W4243112836 created "2022-05-12" @default.
• W4243112836 creator A5073043622 @default.
• W4243112836 creator A5081432266 @default.
• W4243112836 date "2021-08-20" @default.
• W4243112836 modified "2023-09-30" @default.
• W4243112836 title "RETRACTED ARTICLE: Intelligent Decision Making Algorithm for Balanced Cluster Formation in Wireless Sensor Networks" @default.
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• W4243112836 doi "https://doi.org/10.1007/s11277-021-08715-6" @default.
• W4243112836 hasPublicationYear "2021" @default.
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