Abstract
Background: The concern with the IoT node is energy since nodes are depleted as their energy utilization is incrementally reduced with the reduction in far off nodes. The nodes will consume energy when it senses the data, followed with the computation, and further for transmission.
Methods: We proposed the phases for energy-saving at nodes by Enhanced Agglomerative Clustering, Dynamic Selection of Leader, disposal of faraway sensor, and B * tree cloud storage and retrieval. In a typical IoT system, the nodes are deployed in the environment initially. Nodes are clustered using Enhanced Agglomerative Clustering Algorithm. A far node elimination will be implemented for the nodes not in the cluster region.
Results: By eliminating the need of far-off sensors, we can reduce the energy used. This in turn can also improve the life of sensors. When appropriate, sensitive data are moved from IoT devices and stored in the cloud.
Conclusion: This paper also proposes an approach to fetch the data from IoT by using the Query Predicate method. This research work proposes a unique choice of grouping by estimating the parameters as energy, separation, thickness and portability.
Keywords: IoT, far away node, enhanced agglomerative clustering algorithm, DD-IoT, B * tree, RQP.
Graphical Abstract
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