Scientists to tap data networks' hidden powers https://eurekalert.org/pub_releases/2018-07/ru-stt071618.php

1. PUBLIC RELEASE: 16-JUL-2018
Scientists to tap data networks' hidden powers
Rice University researchers win NSF funds to develop distributed programming for speedier analysis
RICE UNIVERSITY
Rice University scientists have been awarded a National Science Foundation grant to develop distributed
programming methods to analyze streaming data.
IMAGE: THIS IS ANG CHEN, LEFT, AND EUGENE NG. view more 
CREDIT: JEFF FITLOW/RICE UNIVERSITY

2. Computer scientists Ang Chen and Eugene Ng will use a three-year, $1.2 million grant to take advantage of
programmable elements in the various components that store and deliver data to customers.
According to Chen, principal investigator on the project, it means the switches, routers and other components
that stand between end users and data servers can play a more active part in managing and analyzing big
data. It could make data networks faster and more e cient, which would be a boon for nancial services,
social networks, the "internet of things" and many other applications.
The researchers said the range of programmable elements in data networks has expanded to include not only
servers but also interface components, eld-programmable gate arrays, application-speci c integrated circuits
and network topology. "Today, all the processing is done at the server, without any processing or computation
along the path. We're going to try to change that," said Ng, a professor of computer science and electrical and
computer engineering.
"Our vision is to optimize all of these components to achieve a sweet spot in the design space for each
application," said Chen, an assistant professor of computer science and of electrical and computer
engineering, who joined Rice in 2017. "We hope to have an approach that can work across di erent kinds of
protocols."
Ng said common examples of streaming data also include fraud detection, monitors and temperature and
other environmental sensors that continuously generate data and send it at high speed to servers from all
over the world. "Our challenge is to develop a scalable platform that allows programmers to derive real-time
insight from data utilizing the technologies we propose," he said.
One likely strategy is to intelligently process and reduce data before it reaches servers, Ng said. That could be
accomplished by programming components along the path to handle as much computation as they're able.
"That can allow server clusters to pull down more data, because you're not just moving data for the sake of
moving it. You're processing it and potentially generating a partial answer to your question.
"I think it's safe to say that there is vast untapped potential in using this emerging hardware for big data
processing - and the key word is 'emerging,'" Ng said. "It's new, so very few people have thought about what it
can do."
The researchers also plan to study how data ows through networks so they can optimize it on the y.
"Sometimes it matters which stu you perform rst," Chen said. "It's not just about where programming
capabilities exist in the network but also about organization of the network itself.

3. "So we're looking at how an underlying physical network can adapt itself and change the network ow to
optimize latency," he said.
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Read the abstract at https://www.nsf.gov/awardsearch/showAward?AWD_ID=1801884&HistoricalAwards=
false.
This news release can be found online at http://news.rice.edu/2018/07/16/scientists-to-tap-data-networks-
hidden-powers/
Follow Rice News and Media Relations via Twitter @RiceUNews.
Related materials:
Ang Chen bio: https://www.cs.rice.edu/~angchen/
Eugene Ng bio: https://www.cs.rice.edu/~eugeneng/
Rice Department of Computer Science: https://csweb.rice.edu/
Rice Department of Electrical and Computer Engineering: https://eceweb.rice.edu/
George R. Brown School of Engineering: https://engineering.rice.edu
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Baker Institute for Public Policy. With 3,970 undergraduates and 2,934 graduate students, Rice's
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4. Media Contact
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