An unusual collaboration between IT researchers and geneticists may hold the key to increasing international internet...
Researchers at the National ICT Australia (NICTA) Research Centre of Excellence have found a way of identifying noise in the optical cables that form the backbone of the internet, thanks to their application of colleagues' genome analysis tools to the problem.
"We developed a way of presenting an optical signal as a two-dimensional image," said researcher Trevor Anderson. "We thought that it would allow us to recognise the 'fingerprint' of the various kinds of optical noise that can interfere with the signal."
But the NICTA researchers were unable to devise a way to analyse the image.
"Fortunately, in the next-door laboratory, NICTA has a team of geneticists analysing vast lengths of genetic code to find patterns of gene sequences that would indicate a tumour," Anderson said. "Dr Adam Kowalczyk looked at our problem and laughed."
"This is easy," Dr Kowalczyk told Anderson. "Biology is so much more complex."
As part of his genetics research, Dr Kowalczyk typically has only a few 'noisy' samples to analyse, compared to the many samples available to the IT researchers. Hence, Dr Kowalczyk suggested using the genetics algorithms on the optical fibre imagery.
The device that resulted from the research, known as a multi-impairment monitor, will be able to increase the speed of long-haul optical fibres by a factor of four. It should cost a few thousand dollars, and will be able to do a job that today costs more than $100,000.
According to Anderson, current tools are only able to gauge whether or not noise is present in the optical fibre.
But the new device is able to identify the various 'fingerprints' that different sources of noise produce in the optical fibres. With the device, users can ascertain exactly what is producing the noise.
Of the top six forms of noise — including optical amplifier noise, unwanted reflections and asymmetrical fibres — the device is currently able to identify four. Anderson expects it to be able to identify all six in the near future.
The device is expected to be market ready in 12 months.