Layered Attractor Selection for Clustering and Data Gathering in Wireless Sensor Networks

In this paper, the authors propose a clustering scheme for Wireless Sensor Networks (WSN) based on a biologically-inspired mathematical model of a gene network, initially introduced in. The aim of this approach is to establish a robust and resilient clustered network which adapts to and quickly recovers from changes in the environment while keeping the network lifetime as high as possible, in regards to depletion of energy. The concept is based on Adaptive-Response by Attractor Selection (ARAS).