Jazz music and Big Data at the TERENA Networking Conference 2013

Nearly 20 years ago, the European Union came into being – this week’s TERENA Networking Conference is taking place in Maastricht where the treaty that created it was signed. Regardless of whether you see the EU as a positive or negative entity in today’s cash strapped times, it’s appropriate that the Trans-European Research and Education Networking Association should meet here to discuss the next wave of Telco innovation. Hopefully this will mean a few extra Euros will be on their way to all of us in the future.

The Opening Reception on Monday featured a jazz performance inspired by the theme of the conference - "Innovating Together". Thanks to an international collaboration of artists and technicians, on-stage musicians performed alongside their 'virtual' band leader, who was in Edinburgh, UK, assisted by LoLA (LOw LAtency audio/visual system). LoLA was developed by GARR, the Italian research and education networking organisation, and the Music Conservatory G. Tartini in Trieste. Using LoLA, performing artists are able to interact in a natural way even if they are thousands of kilometres apart, relying on the high-quality and very large bandwidth connectivity offered by research and education networks which minimise network-related delay and jitter.

 One source of innovation is likely to be data, and lots of it. In a session called ‘Big Data, Big Deal!’, Harold Teunissen of SURFNet looked at the big data problem. He noted that after the arrival of his twins, he found himself faced by a big data problem of his own – over 30,000 family snaps to share, store and manage. “These two changed my big data perspective for ever,” he said.

In the Netherlands, all ICT activities for Higher Education and Research are now brought under the SURF umbrella including cloud, supercomputing and the esciencecentre. But what is big data? NRENs generate 0.3% of worldwide data. Is this data actually big data, or is mainly people using Facebook, Twitter etc. We don’t know. Research is now seen as a generator of big data, but the cost of generating it can be very high. For example, Teunissen noted that 10 billion dollars spent on the Large Hadron Collider to arrive at one bit of information might be seen as a lot of money by some i.e. proving that Higgs particle exists = true. Of course, the story of the LHC and its research is a lot more complex than that.

Big data actually means large volume, generated at a high velocity and in many different forms, such as video, text and images. What customers need to handle this data tends to either be technology and performance OR solutions and ease of use, depending on whether or not they are early adopters.

Taking up the LHC theme, William Johnston of ESnet looked at high energy physics as a prototype for data intensive science, now paying dividends for the teams working on the  Square Kilometre Array and genomics for example. Growth in scientific data follows Moores Law, leading to exponential growth. However, when looking for technological solutions to big data problems, commercial solutions may not be up to the task.“Software testing started 5 years before the LHC turned on. Science is not YouTube and has special requirements,” said Johnston.

Simon Leinen of Swiss NREN, SWITCH asked whether we should in fact make science more like YouTube, so explore using the cloud and existing services? Johnston responded that HEP is looking at its requirements and how these map onto commercial services, but highly parallel flows of data are somewhat unique to HEP (You can read an article about CERN’s cloud choices by David Meyer in Gigaom at http://gigaom.com/2013/05/31/heres-why-cern-ditched-opennebula-for-openstack/). "This may not be the case for other fields, such as environmental modelling", pointed out Johnston. "Joining supercomputers together to work on a problem is not the same as parallel computing."