Communications of the ACM
Fruit Fly Nervous System Provides Insight to Computer Network Problem
Computing has long been used to analyze biological systems, but "we've reversed the strategy, studying a biological system to solve a long-standing computer science problem," says Ziv Bar-Joseph of Carnegie Mellon's School of Computer Science.
Credit: Carnegie Mellon University
Researchers at Carnegie Mellon and Tel Aviv universities are drawing on inspiration from a fruit fly's nervous system to develop models for distributed computer networks.
A fruit fly's nervous system cells organize themselves so that a few cells act as leaders that connect the other nerve cells together. "It is such a simple and intuitive solution, I can't believe we did not think of this 25 years ago," says Tel Aviv's Noga Alon. The researchers found that the fly's nervous system has an efficient design for networks in which the number and position of nodes is unclear, such as in wireless sensor networks, environmental monitoring, and in systems for controlling swarms of robots.
In computing, developers have created distributed systems using a small set of processors that can communicate with all of the other processors in the network, a group known as the maximal independent set (MIS). However, computer scientists have struggled with determining the best way to choose an MIS, but after studying the fly's nervous system, the researchers created a computer algorithm that provides a fast solution to the MIS problem. "The run time was slightly greater than current approaches, but the biological approach is efficient and more robust because it doesn't require so many assumptions," says Carnegie Mellon professor Ziv Bar-Joseph.
From Carnegie Mellon News
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