Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Data networks (2nd ed.)
Probabilistic modelling
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Ant Colony Optimization
A GENERALIZED CONVERGENCE RESULT FOR THE GRAPH-BASED ANT SYSTEM METAHEURISTIC
Probability in the Engineering and Informational Sciences
Trail Blazer: A Routing Algorithm Inspired by Ants
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Networks of Learning Automata: Techniques for Online Stochastic Optimization
Networks of Learning Automata: Techniques for Online Stochastic Optimization
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
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
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
An analytic modelling approach for network routing algorithms that use "ant-like" mobile agents
Computer Networks: The International Journal of Computer and Telecommunications Networking
Convergence results for ant routing algorithms viastochastic approximation
Proceedings of the 13th ACM international conference on Hybrid systems: computation and control
Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions
Information Sciences: an International Journal
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In this article, we provide convergence results for an Ant-based Routing Algorithm (ARA) for wireline, packet-switched communication networks, that are acyclic. Such algorithms are inspired by the foraging behavior of ants in nature. We consider an ARA algorithm proposed earlier by Bean and Costa [2005]. The algorithm has the virtues of being adaptive and distributed, and can provide a multipath routing solution. We consider a scenario where there are multiple incoming data traffic streams that are to be routed to their respective destinations via the network. Ant packets, which are nothing but probe packets, are introduced to estimate the path delays in the network. The node routing tables, which consist of routing probabilities for the outgoing links, are updated based on these delay estimates. In contrast to the available analytical studies in the literature, the link delays in our model are stochastic, time-varying, and dependent on the link traffic. The evolution of the delay estimates and the routing probabilities are described by a set of stochastic iterative equations. In doing so, we take into account the distributed and asynchronous nature of the algorithm operation. Using methods from the theory of stochastic approximations, we show that the evolution of the delay estimates can be closely tracked by a deterministic ODE (Ordinary Differential Equation) system, when the step size of the delay estimation scheme is small. We study the equilibrium behavior of the ODE system in order to obtain the equilibrium behavior of the routing algorithm. We also explore properties of the equilibrium routing probabilities, and provide illustrative simulation results.