Network builds itself from scratch
By
Kimberly Patch,
Technology Research News
Drawing heavily on the chemistry of biology,
researchers from Humboldt University in Germany have devised a way for
electronic agents to efficiently assemble a network without having to
rely on a central plan.
The researchers modeled their idea on the methods of insects and
other lifeforms whose communications lack central planning, but who manage
to form networks when individuals secrete and respond to chemical trails.
The researchers found that what works for ants and bacteria also
works for autonomous pieces of computer code. "The idea is inspired by
chemotactic models of tracking trail formation widely found in insects,
bacteria, [and] slime molds," said Frank Schweitzer, an associate professor
at Humboldt University and a research associate at the Fraunhofer Institute
for Autonomous Intelligence Systems (FHG-AIS) in Germany.
The work could eventually be used for self-assembling circuits,
groups of coordinated robots and adaptive cancer treatments, according
to Schweitzer.
Insect, bacteria and slime mold communities coordinate growth
processes based on interactions among chemical trails left behind by individuals.
The researchers set up a similar network using a computer simulation of
electronic agents moving randomly across a grid containing unconnected
network nodes.
Rather than determining the structure of a network in a top-down
approach of hierarchical planning, agents found nodes and created connections
in a bottom-up process of self-organization.
When an agent happened on a node, it began to produce one of two
simulated chemical trails at a rate that decreased in time. The strength
of the chemical trail also faded as time went by. The key to the self-assembling
network is that the agents are drawn to the chemical trails laid down
by other agents.
The researchers' model contains two types of network nodes --
blue and red. Each agent starts out as a green agent, which lays down
no chemical trails and travels randomly. When an agent happens on a blue
node, it turns blue, and when an agent happens across a red node, it turns
red. Red and blue agents lay down chemical trails that attract agents
of the opposite color.
Over time the model changes from many green agents traveling randomly
to colored agents moving among nodes like traffic in a network. "You see
a network that connects almost all neighboring nodes," said Schweitzer.
The chemical method simultaneously solves the two basic problems
of network self-assembly -- detecting nodes and establishing links between
nodes, Schweitzer said.
This type of network quickly addresses failures and disturbances,
said Schweitzer. "If the position of the nodes is changed, the network
adjusts accordingly. If a link is broken, it will be restored very fast."
The results should assist efforts to use virtual pheromones to
coordinate computer agents and real-world robots, said Schweitzer. Pheromones
are the chemicals used by ants in their networks.
The same principles can be used to develop self-assembling electronic
circuits from building blocks like nanowires, he said.
Self-assembling networks are important, said Tamas Vicsek, a physics
professor at Eotvos University in Hungary. "In fact, networks like the
Internet are being assembled continuously based on their actual performance,"
he said.
The researchers' model is interesting and may provoke useful insights
for those who run networks, said Vicsek. The current model is too complicated
to be widely applied, however, he said.
There have been previous attempts to design network models that
change their structures as a function of time depending on various parameters
of the network, said Vicsek. The researchers' work is different because
they introduce agents into the picture, which is a nice touch, he said.
"This is a direction which is worth developing further," he said.
Schweitzer's research colleague was Benno Tilch of Humboldt University.
They published the research in the August 21, 2002 issue of Physical Review
E. The research was funded by Humboldt University.
Timeline: Unknown
Funding: University
TRN Categories: Artificial Life and Evolutionary Computing;
Multiagent Systems; Networking
Story Type: News
Related Elements: Technical paper, "Self-Assembling of Networks
in an Agent-Based Model," Physical Review E, August 21, 2002.
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March 26/April 2, 2003
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