Thenervous system of the fruit fly ( Drosophila melanogaster )could helpimprove the design of wireless networks, as suggested by a study by Carnegie Mellon University in Pittsburgh (United States) published in the journalScience. Researchers have been inspired by the way this insect arranges its tiny hair-like structures to feel and hear the world.
Specifically, the cells of the fly’s nervous system are organized so that a small number of them function as leaders to provide direct connections with different nerve cells. Researchers have developed the same kind of scheme todistributed computer networks that carry out everyday tasks such as searching the Internet or controlling an airplane in flight. But the method used by the fly’s nervous system to organize itself is much simpler and more forceful than any of those developed by humans.
The researchers used the information on fruit flies to design a distributed computing algorithm and found that it has qualities that make it particularly adaptable to networks in which the number and position of nodes is not fully established. These networks include wireless sensors, such as those for environmental control, or systems for controlling groups of robots.
In the computing world, one step toward creating distributed systems is to find a small group of processors that can be used to communicate quickly with the rest of the processors on the network, which theorists call a maximum independent set (CIM). Each processor in the network is a leader, member of the CIM, or is connected to it, but the leaders are not interconnected.
A similar organization occurs in the fruit fly, which uses tiny “whiskers” to detect the outside world. Each “whisker” develops from a nerve cell, called the sensory organ precursor (POS), that connects with nearby nerve cells, but not with other POS.
For three decades scientists have wondered how processors in a network can choose CIM members. During the larval and chrysalis phases of fly development, the nervous system uses a probabilistic method to select the cells to become POS. In the fly, however, the cells have no information about how they are connected to each other. As various cells self-select as POS, they send chemical signals to nearby cells that inhibit these cells from becoming POS as well. This process continues until all cells are either POS or neighboring a POS and the fly emerges from the pupa state.
The scientists created a computer algorithm based on the fly system and proved that it provides a quick solution to the MIC problem. In this sense, the authors point out that the action time was slightly higher than that of current methods but that the biological method is efficient and more robust.
