Main Article Content
Energy in a wireless sensor network (WSN) is rendered as the major constraint that affects the overall feasibility and performance of a network. With the dynamic and demanding requirements of diverse applications, the need for an energy efficient network persists. Therefore, this paper proposes a mechanism for optimizing the energy consumption in WSN through the integration of artificial neural networks (ANN) and Kohonen self-organizing map (KSOM) techniques. The clusters are formed and re-located after iteration for effective distribution of energy and reduction of energy depletion at individual nodes. Furthermore, back propagation algorithm is used as a supervised learning method for optimizing the approach and reducing the loss function. The simulation results show the effectiveness of the proposed energy efficient network.
How to Cite
Singh, P., & Anil K Ahlawat, V. P. (2022). Designing an Energy Efficient Network Using Integration of KSOM, ANN and Data Fusion Techniques. International Journal of Communication Networks and Information Security (IJCNIS), 9(3). https://doi.org/10.17762/ijcnis.v9i3.2769 (Original work published December 11, 2017)