San Diego County prepares for network overload during major events

In anticipation of the next fire season in San Diego County, researchers and local authorities are building a wireless network to provide better access to live camera feeds of the county’s large swaths of open land.
“San Diegans need somewhere to turn when a natural disaster hits a rural area nearby, in order to make better decisions about what to do next,” said Hans-Werner Braun, a research scientist at the San Diego Supercomputer Center (SDSC) and director of the SDSC-based Applied Network Research group, which operates the High Performance Wireless Research and Education Network (HPWREN). “Until now we have been able to provide that service covering large parts of San Diego’s back-country, but now we need to ensure that during the next crisis, peak demand for our data will not swamp our ability to keep the camera feeds up and running.”
Around 1,000 people will view the camera feeds on a typical day, but that traffic can quickly quadruple during major weather- or fire-related events. During the 2007 Harris Fire, as many as 50,000 visitors pinged the network to watch video feeds in one day.
“It’s very hard to optimize for a system that can jump up to 50 times normal daily users for brief periods of time – and you don’t know which day the disaster will strike,” Braun added.
The University of San Diego’s division of the California Institute for Telecommunications and Information Technology (Calit2) and HPWREN partnered on the project to give residents and emergency responders a more reliable view of the situation on the ground before they arrive on the scene or determine if their home is in danger.
The team says the new infrastructure can handle traffic from hundreds of thousands of visitors and scale even higher with some modifications on the fly during major events. A beta deployment of the system was launched last week
“We expect significant improvement in performance, especially during large-scale events,” said Braun. “Eventually we look forward to integrating more environmental sensors, not just cameras, into the network. We could integrate various other kinds of environmental data to present a collated view of complex situations. Examples are water and air quality, meteorological data, and seismic data. Many such sensors are already in operation on HPWREN.”