'Anternet' discovered: Behavior of harvester ants as they forage for food mirrors protocols that control Internet traffic

ScienceDaily (Aug. 28, 2012) — On the surface, ants and the Internet don't seem to have much in common. But two Stanford researchers have discovered that a species of harvester ants determine how many foragers to send out of the nest in much the same way that Internet protocols discover how much bandwidth is available for the transfer of data. The researchers are calling it the "anternet."

Deborah Gordon, a biology professor at Stanford, has been studying ants for more than 20 years. When she figured out how the harvester ant colonies she had been observing in Arizona decided when to send out more ants to get food, she called across campus to Balaji Prabhakar, a professor of computer science at Stanford and an expert on how files are transferred on a computer network. At first he didn't see any overlap between his and Gordon's work, but inspiration would soon strike.

"The next day it occurred to me, 'Oh wait, this is almost the same as how [Internet] protocols discover how much bandwidth is available for transferring a file!'" Prabhakar said. "The algorithm the ants were using to discover how much food there is available is essentially the same as that used in the Transmission Control Protocol."

Transmission Control Protocol, or TCP, is an algorithm that manages data congestion on the Internet, and as such was integral in allowing the early web to scale up from a few dozen nodes to the billions in use today. Here's how it works: As a source, A, transfers a file to a destination, B, the file is broken into numbered packets. When B receives each packet, it sends an acknowledgment, or an ack, to A, that the packet arrived.

This feedback loop allows TCP to run congestion avoidance: If acks return at a slower rate than the data was sent out, that indicates that there is little bandwidth available, and the source throttles data transmission down accordingly. If acks return quickly, the source boosts its transmission speed. The process determines how much bandwidth is available and throttles data transmission accordingly.

It turns out that harvester ants (Pogonomyrmex barbatus) behave nearly the same way when searching for food. Gordon has found that the rate at which harvester ants -- which forage for seeds as individuals -- leave the nest to search for food corresponds to food availability.

A forager won't return to the nest until it finds food. If seeds are plentiful, foragers return faster, and more ants leave the nest to forage. If, however, ants begin returning empty handed, the search is slowed, and perhaps called off.

Prabhakar wrote an ant algorithm to predict foraging behavior depending on the amount of food -- i.e., bandwidth -- available. Gordon's experiments manipulate the rate of forager return. Working with Stanford student Katie Dektar, they found that the TCP-influenced algorithm almost exactly matched the ant behavior found in Gordon's experiments.

"Ants have discovered an algorithm that we know well, and they've been doing it for millions of years," Prabhakar said.

They also found that the ants followed two other phases of TCP. One phase is known as slow start, which describes how a source sends out a large wave of packets at the beginning of a transmission to gauge bandwidth; similarly, when the harvester ants begin foraging, they send out foragers to scope out food availability before scaling up or down the rate of outgoing foragers.

Another protocol, called time-out, occurs when a data transfer link breaks or is disrupted, and the source stops sending packets. Similarly, when foragers are prevented from returning to the nest for more than 20 minutes, no more foragers leave the nest.

Prabhakar said that had this discovery been made in the 1970s, before TCP was written, harvester ants very well could have influenced the design of the Internet.

Gordon thinks that scientists have just scratched the surface for how ant colony behavior could help us in the design of networked systems.

There are 11,000 species of ants, living in every habitat and dealing with every type of ecological problem, Gordon said. "Ants have evolved ways of doing things that we haven't thought up, but could apply in computer systems. Computationally speaking, each ant has limited capabilities, but the collective can perform complex tasks.

"So ant algorithms have to be simple, distributed and scalable -- the very qualities that we need in large engineered distributed systems," she said. "I think as we start understanding more about how species of ants regulate their behavior, we'll find many more useful applications for network algorithms."

The work is published in the Aug. 23 issue of PLoS Computational Biology.

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The above story is reprinted from materials provided by Stanford University. The original article was written by Bjorn Carey.

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Journal Reference:

Balaji Prabhakar, Katherine N. Dektar, Deborah M. Gordon. The Regulation of Ant Colony Foraging Activity without Spatial Information. PLoS Computational Biology, 2012; 8 (8): e1002670 DOI: 10.1371/journal.pcbi.1002670

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Identical DNA codes discovered in different plant species

ScienceDaily (Apr. 9, 2012) — Analyzing massive amounts of data officially became a national priority recently when the White House Office of Science and Technology Policy announced the Big Data Research and Development Initiative. A multi-disciplinary team of University of Missouri researchers rose to the big data challenge when they solved a major biological question by using a groundbreaking computer algorithm to find identical DNA sequences in different plant and animal species.

"Our algorithm found identical sequences of DNA located at completely different places on multiple plant genomes," said Dmitry Korkin, lead author and assistant professor of computer science. "No one has ever been able to do that before on such a scale."

"Our discovery helps solve some of the mysteries of plant evolution," said Gavin Conant, co-author and assistant professor of animal sciences. "Basic research on the plant genome provides raw materials and improves techniques for creating medicines and crops."

Previous studies found long strings of identical code in different species of animals' DNA. But before this new MU research, which was published in the Proceedings of the National Academy of Sciences, computer programs had never been powerful enough to find identical sequences in plant DNAs, because the identical sections weren't found at the same points.

The genomes of six animals (dog, chicken, human, mouse, macaque and rat) were compared to each other. Likewise, six plant species (Arabidopsis, soybean, rice, cottonwood, sorghum and grape) were compared to each other. Comparing all the genetic sequences took 4 weeks with 48 computer processors doing 1 million searches per hour for a grand total of approximately 32 billion searches.

Although the scientists found identical sequences between plant species, just as they did between animals, they suggested the sequences evolved differently.

"You would expect to see convergent evolution, but we don't," Conant said. "Plants and animals are both complex multi-cellular organisms that have to deal with many of the same environmental conditions, like taking in air and water and dealing with weather variations, but their genomes code for solutions to these challenges in different ways."

The MU team's research laid the groundwork for future studies into the reasons plants and animals developed different genetic mechanisms and how they function. Their basic research created a foundation for discoveries that may improve human life. Besides advancing genetic science's potential to fight disease, the code-analyzing computer program itself could help in the development of new medicines.

"The same algorithm can be used to find identical sequential patterns in an organism's entire set of proteins," said Korkin. "That could potentially lead to finding new targets for existing drugs or studying these drugs' side effects."

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