What the humble fruit fly is teaching the powerful computer

And you thought the fruit fly was just a dirty little pest.

A new study reveals that the fly arranges the hair-like structures of its nervous system to feel and hear. That method now serves as a model for refining wireless sensor networks, among other computer applications.

A study by the team of scientists, including Ziv Bar-Joseph of Carnegie Mellon University, will be published Friday in the journal Science.

The team determined that the fruit fly uses minimal communications without advanced knowledge to arrange the hair-like structures so that a small number of cells emerges as leaders that provide direct connections with every other nerve cell.

This method of organization is simpler than existing systems used to manage the distributed computer networks that perform such functions as searching the Web or controlling airplanes in flight.

"It's such a simple and intuitive solution. I can't believe we did not think of this 25 years ago," said study co-author Noga Alon, a mathematician and computer scientist at Tel Aviv University and the Institute for Advanced Study in Princeton, N.J.

Using the fruit fly as its inspiration, the team produced a distributed computing algorithm that is well suited for networks in which the number and position of nodes is not completely certain. These include wireless sensor networks, such as environmental monitoring, where sensors are dispersed in a lake or waterway, or systems for controlling swarms of robots.

"Computational and mathematical models have long been used by scientists to analyze biological systems," said Dr. Bar-Joseph of CMU's Lane Center for Computational Biology in the School of Computer Science. "Here we've reversed the strategy, studying a biological system to solve a long-standing computer science problem."

Today's large-scale computer systems and the nervous system of a fly both take a distributive approach to performing tasks, a CMU news release explains. Thousands and even millions of processors in a computing system and cells in a fly's nervous system must work together to complete a task. While none of the elements needs to have complete knowledge of what's going on, the systems must function despite failures by individual elements.

The fly's nervous system, as with the team's algorithm, finds a small set of cells -- or processors, in the case of computers -- that can be used to communicate rapidly with the rest of the cells or processors in the network. Every processor is either a leader or attached to a leader.

Until now, computer networks used probability to determine which processor would become a leader, usually based on how many connections each had with other processors. The chance of any processor becoming a leader increases based on the number of its connections.

The human method is fast but entails lots of complicated messages that must be sent back and forth across the network. The processors also must know in advance how they are connected in the network, creating problems in wireless sensor networks where sensors might be distributed randomly and might not be within communication range of each other.

In the fly's nervous system, cells that become leaders send out signals to neighbors that disable them. There is no advanced knowledge of how the cells will be arranged. Communication between the cells determines the arrangement quickly and in simple fashion.

Dr. Bar-Joseph said the algorithm based on the fly's nervous system has produced "a fast solution" to the problem that makes it feasible to use in many network applications.





First published on January 13, 2011 at 2:28 pm