This project studies the design of robust bio-inspired Wireless Sensor Networks (B-WSN) by leveraging optimal results from nature?s computation. Functional robustness of living organisms is often attributed to the optimized structures of their gene regulatory networks (GRNs), which oversee the proper behavior of cells through interactions among different genes. GRNs can adapt to dynamic changes (i.e., perturbations) in the environment, and are resilient to the removal/malfunction of nodes in the network. This project will identify the features intrinsic to GRN based robustness and fault-tolerance and apply them to bio-inspired wireless sensor networks. In particular, teh project will devise suitable mapping between GRNs and WSNs to form the basis of our B-WSN testbed to assess network level robustness of biological systems. The B-WSN will be designed to act as an in silico testbed, where each node can be monitored and GRN-based routing topologies can be modified so that it is possible to demonstrate how specific topological aspects contribute to the robustness of complex systems.
