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 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 emerge as leaders that provide direct connections with every other nerve cell. 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.
In the fly's nervous system, cells that become leaders send out signals to neighbours 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.
One step toward creating this distributive system is to find a small set of processors that can be used to rapidly communicate with the rest of the processors in the network - what graph theorists call a maximal independent set (MIS). Every processor in such a network is either a leader (a member of the MIS) or is connected to a leader, but the leaders are not interconnected.
The researchers created a computer algorithm based on the fly's approach and proved that it provides a fast solution to the MIS problem.
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 in so many network applications
The find indicates similar techniques used to manage the distributed computer networks. However, the fly's nervous system techniques are much simpler and more robust.
Using the fruit fly technique, the team designed a new distributed computing algorithm, which is particularly well suited for wireless sensor networks, such as environmental monitoring, where sensors are dispersed in a lake or waterway, or systems for controlling swarms of robots.
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.
This makes the solution applicable to many more applications. 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.
The system has numerous potential applications including searching the Web, controlling airplanes in flight, or doing environmental monitoring, where sensors are dispersed in a lake or waterway. CMU is already using the system to control swarms of tiny robots.