Summary
The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
K. Akkaya and M. Younis. Energy-aware routing of time-constrained traffic in wireless sensor networks. Journal of Communication Systems, Special Issue on Service Differentiation and QoS in Ad Hoc Networks, 17(6):663–687, 2004.
I. F. Akyildiz and I. H. Kasimoglu. Wireless sensor and actor networks: Research challenges. Elsevier Ad Hoc Network Journal, 2:351–367, October 2004.
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. A survey on sensor networks. IEEE Communications Magazine, 408:102–116, August 2002.
P. J. Bentley, T. Gordon, J. Kim, and S. Kumar. New trends in evolutionary computation. In Congress on Evolutionary Computation (CEC-2001), pages 162–169, Seoul, Korea, May 2001.
E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York, 1999.
D. Culler, D. Estrin, and M. B. Srivastava. Overview of sensor networks. Computer, 378:41–49, August 2004.
S. K. Das, N. Banerjee, and A. Roy. Solving otimization problems in wireless networks using genetic algorithms. In Handbook of Bio-inspired Algorithms. 2004.
L. N. de Castro and J. Timmis. Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Berlin, 2002.
G. Di Caro and M. Dorgio. AntNet: Distributed stigmergetic control for communication networks. Journal of Artificial Intelligence Research, 9:317–365, December 1998.
G. Di Caro, F. Ducatelle, and L. M. Gambardella. AntHocNet: An adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications, Special Issue on Self-organization in Mobile Networking, 16:443–455, 2005.
F. Dressler. Locality driven congestion control in self-organizing wireless sensor networks. In 3rd International Conference on Pervasive Computing (Pervasive 2005): International Workshop on Software Architectures for Self-Organization, and Software Techniques for Embedded and Pervasive Systems (SASO+STEPS 2005), Munich, Germany, May 2005.
F. Dressler. Self-organization in ad hoc networks: Overview and classification. Technical Report 02/06, University of Erlangen, Dept. of Computer Science 7, March 2006.
F. Dressler. Self-Organization in Sensor and Actor Networks. John Wiley & Sons Ltd., West Sussex, 2007.
F. Dressler and B. Krüger. Cell biology as a key to computer networking. In German Conference on Bioinformatics 2004 (GCB’04), Poster Session, Bielefeld, Germany, October 2004.
F. Dressler, B. Krüger, G. Fuchs, and R. German. Self-organization in sensor networks using bio-inspired mechanisms. In 18th ACM/GI/ITG International Conference on Architecture of Computing Systems - System Aspects in Organic and Pervasive Computing (ARCS’05): Workshop Self-Organization and Emergence, pages 139–144, Innsbruck, Austria, March 2005.
M. Eigen and P. Schuster. The Hypercycle: A Principle of Natural Self Organization. Springer, Berlin, 1979.
S. Hofmeyer and S. Forrest. Architecture for an artificial immune system. Evolutionary Computation, 84:443–473, 2000.
C. Intanagonwiwat, R. Govindan, and D. Estrin. Directed diffusion: A scalable and robust communication paradigm for sensor networks. In 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCOM’00), pages 56–67, Boston, MA, USA, August 2000.
J. Kennedy and R. C. Eberhart. Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco, 2001.
J. O. Kephart. A biologically inspired immune system for computers. In 4th International Workshop on Synthesis and Simulation of Living Systems, pages 130–139, Cambridge, Massachusetts, USA, 1994. MIT Press.
J. Kim and P. J. Bentley. The artificial immune system for network intrusion detection: An investigation of clonal selection with negative selection operator. In Congress on Evoloutionary Computation (CEC-2001), pages 1244–1252, Seoul, Korea, July 2001.
J. Kim and P. J. Bentley. An evaluation of negative selection in an artificial immune system for network intrusion detection. In Genetic and Evolutionary Computation Conference (GECCO-2001), pages 1330–1337, San Francisco, CA, July 2001.
J. Kim and P. J. Bentley. Towards an artificial immune system for network intrusion detection. In Congress on Evolutionary Computation (CEC-2002), pages 1015–1020, Honolulu, May 2002.
M. J. B. Krieger, J.-B. Billeter, and L. Keller. Ant-like task allocation and recruitment in cooperative robots. Nature, 406:992–995, August 2000.
B. Krüger and F. Dressler. Molecular processes as a basis for autonomous networking. IPSI Transactions on Advances Research: Issues in Computer Science and Engineering, 11:43–50, January 2005.
T. H. Labella and F. Dressler. A bio-inspired architecture for division of labour in sanets. In 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), Cavalese, Italy, December 2006.
J.-Y. Le Boudec and S. Sarafijanovic. An artificial immune system approach to misbehavior detection in mobile ad-hoc networks. In First International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT2004), pages 96–111, Lausanne, Switzerland, January 2004.
D. W. Lee, H. B. Jun, and K. B. Sim. Artificial immune system for realization of cooperative strategies and group behavior in collective autonomous mobile robots. In 4th International Symposium on Artificial Life and Robotics, pages 232–235, 1999.
J. Suzuki and Y. Yamamoto. Biologically-inspired autonomous adaptability in a communication endsystem: An approach using an artificial immune network. IEICE Transactions on Information and Systems, E84-D(12):1782–1789, December 2001.
H. von Foerster. On self-organizing systems and their environments. In M. C. Yovitts and S. Cameron, editors, Self-Organizing Systems, pages 31–50. Pergamon Press, 1960.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Dressler, F. (2009). Bio-Inspired Networking — Self-Organizing Networked Embedded Systems. In: Organic Computing. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77657-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-77657-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77656-7
Online ISBN: 978-3-540-77657-4
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)