Performance of wireless sensor topologies inspired by E. coli genetic networks

Wireless Sensor Networks (WSNs) form a critical component in modern computing applications; given their size, ability to process and communicate information, and to sense stimuli, they are a promising part of The Internet of Things. However, they are also plagued by reliability and node failure problems. Here we address these problems by using E. coli Gene Regulatory Networks (GRNs) - believed to be robust against signaling disruptions, such as gene failures - to study the transmission properties of randomly-generated WSNs and transmission structures derived from these genetic networks. Selection of sink nodes is crucial to the performance of these networks; here we introduce two sink-node selection techniques: a Motif-based, and a Highest Degree-based approach. Using NS-2 simulations, the performance of both networks is evaluated under varying channel loss models. Successful packet receipts are compared among these networks, which are shown to be higher using GRNs for the communication structure, rather than randomly generated WSNs. This work paves the way for future development of fault-tolerant and robust WSN deployment and routing algorithms.