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Designing interconnected networks for improving robustness and efficiency

The Internet is rapidly developing toward the next generation of the Internet of Things (IoT), which accelerates the emergence of interconnected network architectures even further. However, the way to design interconnected networks that can meet various changes in environment and service demands remains an important issue that has not been appropriately addressed yet. These interconnected networks should be robust to suppress or prevent diffusion of malicious information, whereas they should also be efficient to enhance diffusion of urgent information throughout the entire network. In this study, we propose a Network of Networks (NoN) model inspired by the modularly interconnected networks in the brain, and show that the model has two prominent characteristics. First, unintentional information diffusion from one subnetwork to another can be prevented. Second, speed of information diffusion can be controlled even when the diffusion starts from interconnecting links across two subnetworks. For the second point, we further investigate a strategy for influencing the information diffusion speed by appropriately configuring the connectivity within and between subnetworks. Simulation experiments confirm that by adapting the brain-inspired activation rules on the interconnecting links, our model is able to switch from the unhindered and fast information diffusion between subnetworks to the slow case where all interconnecting links are inoperative.