A Novel Approach for Energy Efficient Cluster-based In-Network Data Fusion (CBDF) in Wireless Sensor Networks (WSN)
Keywords:Wireless Sensor Network, Data aggregation, In-network data fusion, Clustering, Cluster Head
In recent days, the usability of Wireless Sensor Network (WSN) has been immense in various applications, including environmental monitoring, disaster management, medical observance, military application, etc. WSN is a collection of numerous wireless sensor nodes interconnected with one another. It is widely used for sensing, communicating, and computing data efficiently. WSN is famous for its salient features like efficiency, minimum cost, flexibility, and ease to use. However, it is subject to severe challenges, especially in consuming enormous energy and minimum network lifetime. We proposed a Cluster-based In-Network Data Fusion (CBDF) for WSN. The proposed work is developed to minimize data fusion and clustering energy consumption. In WSN, if the in-network data fusion cannot minimize outgoing data size, it is a critical issue. The proposed CBDF restructures the network into multiple clusters based on its size. As a result, each cluster can communicate with the data fusion center in a synchronized approach. An optimization approach is used to reduce the distance of intra-cluster communication. The proposed structure is compared to other current data aggregation structures, and simulation results show that using the data aggregation process, the proposed approach successfully minimizes energy consumption and delays.
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