Division of labour is one of the possible strategies to efficiently exploit the resources of autonomous systems. It is also a phenomenon often observed in animal systems. We show an architecture that implements division of labour in Sensor/Actuator Networks. The way the nodes take their decisions is inspired by ants’ foraging behaviour. The preliminary results show that the architecture and the bio-inspired mechanism successfully induce self-organised division of labour in the network. The experiments were run in simulation. We developed a new type of simulator for this purpose. Key features of our work are cross-layer design and exploitation of inter-node interactions. No explicit negotiation between the agents takes place.
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References
Akyildiz, I., Kasimoglu, I.: Wireless sensor and actor networks: research challenges. Ad Hoc Networks 2 (2004) 351-367
Cardei, M., Wu, J.: Coverage in Wireless Sensor Networks. In Ilyas, M., ed.: Handbook of Sensor Networks. CRC Press, West Palm Beach, FL (2004)
Labella, T., Dorigo, M., Deneubourg, J.L.: Division of labor in a group of robots inspired by ants’ foraging behavior. ACM Transactions on Autonomous and Adaptive Systems 1 (2006)4-25
Labella, T., Dorigo, M., Deneubourg, J.L.: Efficiency and task allocation in prey retrieval. In Ijspeert, A., Murata, M., Wakamiya, N., eds.: Biologically Inspired Approaches to Advanced Information Technology: First International Workshop, BioADIT 2004. Volume 3141 of Lecture Notes in Computer Science., Springer Verlag, Heidelberg, Germany (2004)
Dressler, F.: Self-Organization in Ad Hoc Networks: Overview and Classification. Technical Report 02/06, University of Erlangen, Dept. of Computer Science 7 (2006)
Gerkey, B., Matarić , M.: A market-based formulation of sensor-actuator network coordination. In Sukhatme, G., Balch, T., eds.: Proceedings fo the AAAI Sping Symposium on Intelligent Embedded and Distributed Systems, AAAI Press, San Jose, CA (2002) 21-26
Younis, M., Akkaya, K., Kunjithapatham, A.: Optimization of Task Allocation in a Cluster-Based Sensor Network. In: Proceedings of the Eighth IEEE Symposium on Computers and Communications (ISCC 2003), IEEE Computer Society, Los Alamitos, CA (2003)329-334
Batalin, M., Sukhatme, G.: Using a sensor network for distributed multi-robot task allocation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA2004). Volume 1., IEEE Press, New York, NY (2004) 158-164
Low, K., Leow, W., Ang, M.: Autonomic mobile sensor network with self-coordinated task allocation and execution. IEEE Transactions on Systems, Man and Cybernetics, Part C 36 (2006) 315-327
Bonabeau, E., Theraulaz, G., Deneubourg, J.L.: Quantitative study of the fixed threshold model for the regulation of division of labor in insect societies. Proceedings of the Royal Society of London, Series B-Biological Sciences 263 (1996) 1565-1569
Jesi, G., Montresor, A., Babaoglu, O.: Proximity-aware superpeer overlay technologies. In Keller, A., Martin-Flatin, J.P., eds.: Proceedings of SelfMan’06. Volume 3996 of Lecture Notes in Computer Science., Springer Verlag, Heidelberg, Germany (2006) 43-57
Labella, T., Dietrich, I., Dressler, F.: BARAKA: A hybrid simulator of sensor/actuator networks. In: Proceedings of the Second IEEE/Create-Net/ICST International Conference on COMmunication System softWAre and MiddlewaRE (COMSWARE 2007), Bangalore, India (2007)
Jakobi, N., Husbands, P., Harvey, I.: Noise and the reality gap: the use of simulation in evolutionary robotics. In Moran, F., Moreno, A., Merelo, J., Chacon, P., eds.: Advances in Artificial Life: Proceedings of the Third European Conference on Artificial Life. Volume 929 of Lecture Notes in Computer Science., Springer Verlag, Heidelberg, Germany (1995)704-720
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York (1999)
Abolhasan, M., Wysocki, T., Dutkiewicz, E.: A review of routing protocols for mobile adhoc networks. Ad Hoc Networks 2 (2004) 1-22
Di Caro, G., Ducatelle, F., Gambardella, L.: 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 (2005) 443-455
Perkins, C., Royer, E.: Ad hoc On-Demand Distance Vector Routing. In: 2nd IEEE Workshop on Mobile Computing Systems and Applications, IEEE Computer Society, Los Alamitos, CA (1999) 90-100
Balch, T.: Hierarchic social entropy: An information theoretic measure of robot group diversity. Autonomous Robots 8 (2000) 209-238
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Labella, T.H., Dressler, F. (2007). A Bio-Inspired Architecture for Division of Labour in SANETs. In: Dressler, F., Carreras, I. (eds) Advances in Biologically Inspired Information Systems. Studies in Computational Intelligence, vol 69. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72693-7_11
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