Topology distribution cost vs. efficient routing in large networks
SIGCOMM '90 Proceedings of the ACM symposium on Communications architectures & protocols
Networking with Cognitive Packets
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
QoS-based Routing in Networks with Inaccurate Information: Theory and Algorithms
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
International Journal of Communication Systems
LCN '07 Proceedings of the 32nd IEEE Conference on Local Computer Networks
Ants and reinforcement learning: a case study in routing in dynamic networks
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Ant colony optimization for routing and load-balancing: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A state-dependent time evolving multi-constraint routing algorithm
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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This paper introduces a polynomial time approximation Quality of Service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize the end-to-end delay packet transmission. The algorithm presented here is based on our earlier adaptive routing system and uses a model combining both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Numerical results obtained with OPNET simulator for different levels of traffic's load show good performances of our approach compared the classical non adaptive algorithms in a high dynamic environment.