Data Accuracy Model for Distributed Clustering Algorithm Based on Spatial Data Correlation in Wireless Sensor Networks

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The main objective of this paper is to construct a distributed clustering algorithm based upon spatial data correlation among sensor nodes and perform data accuracy for each distributed cluster at their respective cluster head node. The authors investigate that due to deployment of high density of sensor nodes in the sensor field, spatial data are highly correlated among sensor nodes in spatial domain. Based on high data correlation among sensor nodes, they propose a non-overlapping irregular distributed clustering algorithm with different sizes to collect most accurate or precise data at the cluster head node for each respective distributed cluster.