A Bio-inspired Approach to Design Robust and Energy-efficient Communication Network Topologies

With the advent of Internet of Things (IoT), sensor networks are being utilized widely for data collection and dissemination. In order to ensure seamless communication, it is imperative to design topologically robust and energy-efficient networks. In this work, we introduce bio-inspired approaches for network topology construction based on the innate graph robustness of a biological network called the Gene Regulatory Network (GRN). We briefly discuss some of the topological properties of GRN, followed by its application in the design of wireless sensor network, disaster response network as well as a distributed event sensing and data collection framework for IoT and smart city applications. Finally, we demonstrate some graph experimental results that suggest that our proposed bio-inspired solutions exhibit greater robustness compared to existing graph topologies.