Applying T-norm fuzzy logic to the sensor selection problem in WSNs

The challenges involved in the application of fuzzy logic in wireless sensors networks often stem from the limitation in processing and storage capabilities of the nodes. This anomaly can be overcome by using a centralized data sink, equipped with more storage and processing capabilities and which can also serve as the decider on the occurrence or otherwise of the event of interest based on selected readings of a subset of the deployed nodes. It is known that selecting a finite subset of a universal set can be intractable especially with relatively large size of the problem space. In this paper, we propose the application of T-norm Fuzzy Logic(TFL) to address the sensor selection problem and compare its performance to that of a standard Genetic Algorithm (GA). Extensive simulation results reveal the usefulness of this approach and how it is closely related to the GA technique.