Ant Colonies Offer Network Solutions

Anyone who has spent time gazing at a colony of zigzagging ants has probably noticed the insects are all about teamwork.

Working together, a swarm of ants can haul a piece of food 10 times their size up a steep slope. And, somehow, workers streaming to and from the nest always seem to settle on the shortest path to a food source.

Recently engineers have taken notice of the insects’ impressive use of collaboration and have started finding ways to apply it to problems in the world of humans.

“Ants have been around for 50-90 million years,” says Eric Bonabeau, a telecommunications engineer and biologist who conducted studies on ant colonies at the Sante Fe Institute. “That might be the reason why they’ve got a good system down that doesn’t require complex units.”

Collective Intellect

The ant, itself, Bonabeau points out, is not a complex unit. In fact, all of its movements are based on immediate reactions to its surroundings or to its fellow ants. Put those ants together, however, and a sophisticated system emerges. Some scientists call it a collective intelligence.

Take, for example, the ability of ants to find the shortest path to a food source. When an obstacle, such as a stick or even a person’s foot, blocks the most direct path, ants very quickly find the next best route.

Translate that ability to glitches on the Internet or roadways or in telephone lines and the ant can offer some solutions. If the nodes on one Internet network are clogged with too much traffic, it’s sometimes necessary to reroute new traffic. The same problem occurs with telephone lines that become tied up or trucking routes that become congested by holiday traffic.

Ants get around the problem by laying down a thin layer of signaling chemicals called pheromones wherever they travel. When other ants detect these pheromones, they instinctively follow the path the chemicals mark. The thicker the pheromone trail, the more likely other ants will follow the path.

Because the ants that follow the shortest path are also those first to make a return trip to the food source, their pheromone trail quickly becomes thicker. The heavier pheromone scents attract more ants and the shortest path is even further reinforced.

Meanwhile, there are always some ants that follow their own trail and explore new routes. These individuals also lay pheromone trails as they go. So when, say, a rock tumbles across the main route and traffic is jammed, the ants are ready with a backup path. Rarely used, inefficient routes are eventually abandoned as the pheromone trails marking them evaporate.

“Ants are not adaptive, themselves,” explains Marco Dorigo, a computer scientist at the Universite Libre de Bruxelles in Brussels, Belgium, and coauthor with Bonabeau of a study on ant swarming in this week’s issue of Nature. “It is the ant colony as a whole that adapts to the changing problem.”

To build on the technique that they observed in ants, Dorigo and Bonabeau devised a system they call the Traveling Salesman Problem. In this scenario, virtual ants travel to every point on a given electronic map. When they reach a node that is highly useful (by offering say, a traffic-free zone or a powerful connector) they are programmed to release more virtual pheromones. Other virtual ants then follow this preferred route and eventually the best path is mapped out on the network.

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