Robust Design of Wireless Sensor Networks using Gene Regulatory Networks

Sensor nodes in Wireless Sensor Network (WSN) are responsible for sensing the environment and propagating the collected data in the network. The communication between sensor nodes may fail due to different factors, such as temporal variations of the wireless channel, interference, hardware failures, and energy depletion. Hence, robust design of WSNs in order to be resilient to such failures is an important challenge. In my work, I exploit real biological gene structure to design wireless sensor networks. More specifically, Gene Regulatory Network (GRN) of the real living organisms which has been evolved over millions of years, display intrinsic properties of adaptation and robustness and make them suitable for dynamic network environments. The main purpose of this work is to use the robust GRN topology as a template to design communication structure of the WSN. Hence, the resultant WSN called bioinspired WSN inherits the robustness properties of the GRN topology.