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Hierarchical autoregressive bidirectional least-mean-square algorithm for data aggregation in WSN based IoT network by Mahesh N; Vijayachitra S is a Engineering article available to read on EtoBox.

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The Internet of Things (IoT) is emerging that acquired the interest of several researchers, as it inspires each object to offer services and data to users by collaborating with each other. The Wireless sensor network (WSN) is a major constituent of IoT in transmitting data. Various wireless sensor-based protocols are developed for path selection. This paper develops a data aggregation technique using an optimization model for WSN-based IoT network. The overall procedure involves simulation of WSN-based IoT, multipath routing and finally, data aggregation. At first, the WSN-based IoT nodes are simulated, which are subjected to a multipath routing process. The multipath routing is done using DEMFO, which is devised by combining Dolphin Echolation (DE) and Moth fly optimization technique (MFO). From the obtained paths, the data routing is performed wherein data are subjected to the base station. In the base station, the data aggregation is done using the proposed Hierarchical autoregressive Bidirectional Least-Mean-Square algorithm (HABLMS). The proposed HABLMS is devised by combining Hierarchical autoregressive (HA) using the Caviar model and Bidirectional Least-Mean-Square algorithm

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Author

Mahesh N; Vijayachitra S

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Engineering (Physical Sciences)