Editorial: Biologically Inspired Networking
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Editorial: Biologically Inspired Networking Tadashi Nakano 1 & Adriana Compagnoni 2
# Springer Science+Business Media, LLC, part of Springer Nature 2019
Editorial: Biologically inspired networking is the emerging interdisciplinary research field that seeks the understanding of key principles, processes and mechanisms in biological systems and leverages the understanding to develop novel networking mechanisms. To highlight recent advances in biologically inspired networking, we have organized the special issue based on selected papers presented at the 10th EAI International Conference on Bioinspired Information and Communications Technologies (March 15–16, 2017 Hoboken, New Jersey, USA). We have also solicited papers through an open call and included in the special issue after rigorous review. As a result, we have selected 6 papers for inclusion in the special issue. The brief summary of these papers is given in the following. In the first article titled “From Blindness to Foraging to Sensing to Sociality: an Evolutionary Perspective on Cognitive Radio Networks”, Wisniewska et al. introduce the new notion of evolutionary pressures in cognitive radio societies and show how it can drive the emergence of advanced sensing capabilities and sophisticated resource sharing. In particular, they consider biologically inspired evolutionary stages of cognitive radio societies: consuming, foraging, contention-sensing, and sociality, and demonstrate that, at each stage of evolution, a subpopulation performs more advanced sensing and extract greater utility from spectrum resources. Through mathematical modelling and analysis, they identify critical factors that accelerate or inhibit evolution of cognitive radio societies. The second article, “A Chemical Reaction Algorithm to Solve the Router Node Placement in Wireless Mesh Networks” by Sayad et al., considers the router node placement in wireless mesh networks. Specifically, this paper considers the
* Tadashi Nakano [email protected] 1
Institute for Datability Science, Osaka University, Osaka, Japan
2
Department of Computer Science, Stevens Institute of Technology, Hoboken, NJ, USA
following problem: given a set of mesh clients deployed in a rectangular area, determine the best placement of mesh routers so that both client coverage and network connectivity are maximized. To solve this problem, a metaheuristic technique is inspired based on the observation that, in chemical reactions, molecules interact to reach a low stable energy state. Simulation results are provided to demonstrate that the proposed bioinspired algorithm outperforms the existing genetic algorithm and simulated annealing. In the third article titled “A Cognitive Routing Protocol for Bio-Inspired Networking in the Internet of Nano-Things (IoNT)”, Al-Turjman proposes a framework for data delivery in nano-scale networks. The proposed framework facilitates the development of energy-efficient applications in the Internet of Nano Things (IoNT) where data is relayed via nano-routers from multifarious nano
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