Tuesday, 26 August 2008

Wireless sensors learn from life - Self Assembly Networks

Original Article

PhysOrg.com) -- European and Indian researchers are applying principles learned from living organisms to design self-organising networks of wireless sensors suitable for a wide range of environmental monitoring purposes.

Monsoon rains in the Indian state of Kerala often bring increased risk of landslides. What can be done to warn nearby communities that a landslide is imminent?

One answer is to use a wireless sensor network to monitor geological conditions. Wireless sensors are becoming popular because the sensor nodes are small, simple and cheap and require no cabling to connect them together and to the control centre. They can be used for numerous purposes and are well suited to environmental monitoring.

There are downsides, though. Sensors and communication links can fail, and the nodes rely on battery power. Large networks can become congested with many sensors reporting at the same time to the same control centre.

However, what matters is not so much the reliability of the individual sensors but the reliability of the network as a whole. Does this system reliably monitor air pollution in the city centre? Does that system reliability measure weather conditions on the motorway bridge?

Biological analogy

These are the kinds of problems being tackled by WINSOC, an EU-funded project to find new ways of organising wireless sensor networks to make them robust against node failures and capable of being implemented on large scales.

What makes WINSOC different from earlier projects is that it has taken its cue from biological systems. Where sensor networks are made up of many individual sensors, living organisms are made up from many individual cells.

“Living systems are intrinsically robust against cells dying or being damaged,” says Sergio Barbarossa of the University of Rome 'La Sapienza', who is the scientific coordinator of WINSOC. “The behaviour of most organs is an emerging feature, resulting from the interaction of many cells, where no cell is particularly robust or even aware of the whole behaviour.”

A striking example is the rhythm of the heart, which is controlled by the interaction of several pacemaker cells, each of which can be seen as a pulse oscillator. Even though individual oscillators are not particularly stable or reliable, the heart as a whole is extremely stable and can readily adapt to changing conditions.


“The starting point in WINSOC was to provide mathematical models of biological systems and translate them into algorithms to determine how the sensor nodes should interact with each other,” says Barbarossa.

A prototype sensor node is being developed, but the challenge is to make the network able to continue to function even when several sensors fail.

The answer is self-organisation. In the WINSOC approach, sensor nodes communicate with their neighbours to arrive at a consensus on what has been sensed. The network then finds the best path through the available nodes to relay this information to the control centre.

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