Ant algorithms for discrete optimization
Artificial Life
ARA - The Ant-Colony Based Routing Algorithm for MANETs
ICPPW '02 Proceedings of the 2002 International Conference on Parallel Processing Workshops
WIMOB '06 Proceedings of the 2006 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
A learning automata-based fault-tolerant routing algorithm for mobile ad hoc networks
The Journal of Supercomputing
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The fault-prone nodes in mobile ad-hoc networks (MANETs) degrade the performance of any routing protocol. Using greedy routing mechanisms that tend to choose a single path every time, may cause major data losses, if there is a breakdown of such a path in a fault-prone environment. On the other hand, using all the available paths causes an undesirable amount of overhead on the system. Designing an effective and efficient fault-tolerant routing protocol is inherently hard, since the problem is NP-complete, due to the unavailability of precise path information in adversarial environments [1]. To address the challenges of effective fault-tolerant routing, we present a fault-tolerant routing algorithm (FTAR), based on the ideas of how swarms of natural ants operate[2]. The algorithm is divided into various stages namely initialization, path selection, pheromone deposition, confidence calculation, evaporation and negative reinforcement. Simulation results show that FTAR achieves high packet delivery ratio and throughput as compared to some of the key protocols which do not do fault-tolerance at all. Most importantly, FTAR beats the best fault-tolerant MANET routing algorithm [1] known currently, with respect to the amount of routing overhead incurred, which is an important consideration.