Abstract
Minimal energy consumption and maximal event detection rate are among the main objectives in Wireless Sensor Networks (WSN). Sensor nodes are constrained units that have limited energy and low processing capabilities. Some challenging applications aim to spread a large number of nodes randomly in a geographical location to monitor it. Since it is difficult to access frequently and physically these sensors, an independent, failures resistant and distributed control, that is non-assisted by humans is mandatory. However, any intelligent strategy in WSN should have minimal requirements and low overhead. In this paper, we exploit the cell/node analogy to introduce a bio-inspired controller based on the principles of Gene Regulatory Network (GRN). This controller is adapted by the Genetic Algorithm. By implementing this controller in each node, the emergent network is characterized by an auto-organized, robust and adaptive behavior similar to a biological system. We compare the approach to a classical approach that uses redundancy as a failure resistance strategy, and found a significant increase in lifetime and event detection rates of the entire network.
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El-Mawass, N., Chendeb, N., Agoulmine, N. (2014). Robust Self-organized Wireless Sensor Network: A Gene Regulatory Network Bio-Inspired Approach. In: Pan, JS., Krömer, P., Snášel, V. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-01796-9_11
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DOI: https://doi.org/10.1007/978-3-319-01796-9_11
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