Ant-link Agents for Load Balancing in Telecommunications Networks Nathan Lindle Xiaofeng Tao Based on the paper by Ruud Schoonderwoerd, Owen Holland, and Janet Bruten

The Problem Congested network is causing dropped calls and disconnects. Surges in demand from certain areas makes the location of congestion unpredictable.

Load Balancing Large telecommunications networks require distribution of calls across all nodes for improved efficiency Two general categories - Pre-specified routing - Dynamic routing

Appleby/Steward Agents Original Mobile Agent System Load management agents launch from a source node and report the best route from every node to the source node Parent agents measure network congestion and distribute load management agents accordingly

Maybe Ants Could do Better The system is expensive and is based mostly in AI and heuristics An ant system needs to simulate the pheromones that ants drop without using too many system resources. They can alter the routing tables of each node based on the age of the ants.

Probabilistic Decision Making The routing tables are altered with the formula Then the entries are normalized by taking 5% noise model added

Finding the Shortest Paths Using this system, a simulation was run to test if the ants could find the shortest path for a given network.

Adding Congestion Increasing the ants age was found to be the best way to take congestion into account. Keeping the ants at one site has another subtle effect

Improved Appleby/Steward Eliminating circular routes by updating routes only in the direction of the source node and having each node contain at most one agent Eliminating excessively long routes by creating a bias for shorter routes

Simulation Each node is issued a demand weight from .01 to .07 which is then normalized (simulates random call distribution) Each node has a call capacity of 40 calls Links between nodes have unlimited capacity

Experiment The system was tested first without changing the distributions

Experiment Cont. They then tested the system with changing distributions.

Conclusion The paper concludes by saying that further study is being conducted to find out if this system will work with an actual network and how it deals with failure. Questions?