A taxonomy of biologically inspired research in computer networking |
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Authors: | Michael Meisel Vasileios Pappas Lixia Zhang |
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Affiliation: | 1. University of California, Los Angeles, Department of Computer Science, Los Angeles, CA 90095, USA;2. IBM T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY 10598, USA;1. Facoltà di Ingegneria, Università Telematica Internazionale Uninettuno, Corso Vittorio Emanuele II 39, 00186 Rome, Italy INFN Sezione Roma Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy;2. Dipartimento di Matematica e Fisica, Università Roma Tre, 84 Via della Vasca Navale, I-00146 Rome, Italy;3. National Institute of Geophysics, Georgian Academy of Sciences, 1 M. Alexidze St., 009 Tbilisi, Georgia;1. Department of Computer Science, University of Almería, 04120, Spain;2. Department of Automation and Systems Engineering (DAS), Federal University of Santa Catarina, Santa Catarina, CEP 88040-970, Brazil;3. Department of Computer and Systems Engineering, University of Murcia, 30100, Spain;1. Konputazio Zientziak eta A. A. Saila, Informatika Fakultatea, UPV/EHU, E-20018 Donostia-San Sebastián, Spain;2. Departamento de Matemáticas, Universidad Carlos III de Madrid, Leganés (Madrid), Spain |
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Abstract: | The natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the inherent challenges of surviving in such a world, biological organisms evolve, self-organize, self-repair, navigate, and flourish. Generally, they do so with only local knowledge and without any centralized control. Our computer networks are increasingly facing similar challenges as they grow larger in size, but are yet to be able to achieve the same level of robustness and adaptability. Many research efforts have recognized these parallels, and wondered if there are some lessons to be learned from biological systems. As a result, biologically inspired research in computer networking is a quickly growing field. This article begins by exploring why biology and computer network research are such a natural match. We then present a broad overview of biologically inspired research, grouped by topic, and classified in two ways: by the biological field that inspired each topic, and by the area of networking in which the topic lies. In each case, we elucidate how biological concepts have been most successfully applied. In aggregate, we conclude that research efforts are most successful when they separate biological design from biological implementation – that is to say, when they extract the pertinent principles from the former without imposing the limitations of the latter. |
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