02-11-2012, 01:05 PM
Ant Colony Optimization for ad-hoc networks
Ant Colony Optimization.pdf (Size: 4.55 MB / Downloads: 34)
· ACO algorithms are inspired by the observation of real
ants (Dorigo, Colorni, Maniezzo, 1991)
· Real Ants are social insects organized in colonies.
· Ant colonies show a high structural level compared to the
simplicity of the single individual
· Ants coordinate their activities by an indirect form of
communication (stigmergy) based on pheromone laying
· Foraging behavior: searching for food by parallel
exploration of the environment
AntNet
AntNet is an instance of an ACO algorithm for: distributed and
adaptive routing in communications networks
•In distributed adaptive routing at each network node the routing
policy is continually adapted to the variations in the input traffic
patterns
•A routing policy is a local mapping parametrized by a data
structure called routing table
•It is assumed that a robust model of the input traffic is not
available: the policy should be learned
AntNet THE ALGORITHM
• Ants are launched at regular instants from each node to
randomly chosen destinations
• Ants are routed probabilistically with a probability function of:
(i) some artificial pheromone values, and
(ii) some heuristic values, maintained on the nodes
• Ants memorize visited nodes and elapsed times
• Once reached their destination nodes, ants retrace their
paths backwards, and update the routing tables
AntNet is distributed and not synchronized