Monday, July 18, 2016

Network designers can learn a lot of ants – IDG.se

It may be useful to study how the ants take decision about where stacks should be placed. Based on such observations, believe scientists at the University of MIT in the United States that it is possible to find better ways to retrieve data from distributed network of sensors.

It turns out that how often explores the ants bump into each other in the quest for a new place for a stack is a good indication of how many are exploring ants that examines a specific location.

When enough exploring ants collected in a place so raises worker ants the queen and carries her to the selected location. Apparently giving random collisions during utforskarmyrornas walks em idea of ​​when a critical mass has arisen regarding interest in a new location.

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graduate student Cameron Musco at MIT and his colleagues have imitated the behavior of ants in a mathematical model. In taking random walks place in an area that is divided into nodes. Each node is connected to several other nodes. When you unleash “model ants” in the model, it appears that, based on how often they collide with each other, relatively quickly get a reliable idea of ​​how many ants in the area.

These findings can applied to the network of sensors, in order to organize efficient data retrieval. For example, sensors that collect data on humidity can send messages to each other in a random way. After a while, one of the sensors send data on the number of sensors that measure the values ​​that exceed a certain limit. It would give a reliable indication of the humidity reached a certain level in the area.

This method requires no central point that all sensors must be connected to, leading simpler network design and easier communication.

According to Cameron Musco, the “random walks” provide about as reliable estimates as random selection by retrieving data from randomly selected sensors in a network.

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Myrmetoden should be useful in environments where the absence of a detailed list of the nodes in a network. An example is if you want to map the opinions of the social network and do not have a list of people included. In a random walk, you can move from one individual to his contacts and on to their contacts, and so on, and count the occurrences of opinions over time.

That it can be both legal and moral grounds to be careful åsiktsregistrering withstand understood to be thought of.

Myrmetoden to collect data is just one example of how MIT explores how biological phenomena are related to computer science.

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