Innovation Award
April 2006
Number 3 |
Finding the fastest route between two nodes of a network is a difficult problem to solve using deterministic algorithms.
An alternative means to solve this problem is to use fuzzy logic solutions. One kind of fuzzy logic solution consists on training neural networks to evaluate multiple routes, and then pick the route which yields the best results after a significant training period.
This class simulates a network router using neural networks to find the fastest gateway port to deliver packets to the final network destination.
Despite the routing solution that is evaluated on each moment may not be necessarily the best, continued training a neural networking may not only improve the solution over time, but may also automatically solve the problems caused by temporary or permanent connectivity interruptions in other routers in the way to the destination of each packet.
Manuel Lemos |
This class can be used to simulate the decision of routing packets of information to reach a given network destination.
It trains a neural network to be able to determine which of the available outbound ports on a network origin node can deliver information packets faster to a given network destination node.
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| File |
Role |
Description |
 neuron.php |
Class |
ANN Router Simulation |
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