Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Proceedings of the Third European Conference on Advances in Artificial Life
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Optimization of Task Allocation in a Cluster-Based Sensor Network
ISCC '03 Proceedings of the Eighth IEEE International Symposium on Computers and Communications
Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Proximity-aware superpeer overlay topologies
SelfMan'06 Proceedings of the Second IEEE international conference on Self-Managed Networks, Systems, and Services
Autonomic mobile sensor network with self-coordinated task allocation and execution
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
QoS-aware ant routing with colored pheromones in wireless mesh networks
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Hybrid simulation of Sensor and Actor Networks with BARAKA
Wireless Networks
Bio-inspired networking: from theory to practice
IEEE Communications Magazine
A state-dependent time evolving multi-constraint routing algorithm
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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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 if inter-node interactions. No explicit negotiation between the agents takes place.