Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/16473
Title: Increasing wireless sensor network lifetime through the application of SOM neural networks
Authors: Cordina, Mario
Debono, Carl James
Keywords: Wireless sensor networks
Self-organizing maps
Neural networks (Computer science)
Energy consumption
Conformal mapping
Issue Date: 2008
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Cordina, M., & Debono, C. J. (2008). Increasing wireless sensor network lifetime through the application of SOM neural networks. 3rd International Symposium on Communications, Control and Signal Processing, St. Julians. 467-471.
Abstract: Wireless sensor networks are an emerging technology that have garnered significant research attention due to their extensive ability to monitor the physical world and their applicability to an extensive range of applications. These networks are generally battery powered making the lifetime of the network a major concern. This energy consumption problem can be mitigated to some extent through the use of energy-aware cluster-based routing algorithms. This work presents a novel cluster-based routing algorithm based on self-organizing map (SOM) neural networks. This solution optimizes the network in clusters in an attempt to balance the energy and reduce the transmission power required by the nodes. Results show that through the application of this optimization technique the system’s lifetime is increased by 57% (in terms of First Node Dies) when compared to LEACH.
URI: https://www.um.edu.mt/library/oar//handle/123456789/16473
Appears in Collections:Scholarly Works - FacICTCCE

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