Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach
DOI:
https://doi.org/10.18486/ijcsnt/5.1.060Keywords:
Wireless, WSN, Cognitive Network, Fuzzy LogicAbstract
The Adaptive Cognitive System (ACS) presented here is based on the concept of cognition applied to Wireless Sensor Networks (WSN) concerning aspects related to memory, history and decision making over network node tasks. The use of cognitive features in the WSN scope allows the nodes to make better decisions about conflicts or anomalies arising from node or route failures that probably will affect the performance network as a whole. Moreover, with the use of cognitive aspects in feedback processes to make decisions in a multilayer approach, it is possible to obtain an improvement in the data transmitted end-to-end by the nodes. The decision process consists of adjustments in memory, queue, route protocols and energy consumption. A Fuzzy Inference System (FIS) is proposed for decision making from the vector collected from the network, and this logic determines the adjustments to be applied to the network. This inference system is expandable, allowing other rules, metrics and parameters to be added to the analysis for more flexibility and improved performance.
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Copyright (c) 2026 Marcel Stefan Wagner, Miguel Arjona Ram´ırez, Wagner Luiz Zucchi
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