System Processing: Hopkins Engineers Design Software to Reduce Page Load Time
For many online consumers, convenience and speed can make or break a purchase. A recent study by Imperva Incapsula reported that seven percent of online consumers said the web page must load immediately or they lose interest in the purchase. Thirty-five percent said they’d wait between three and five seconds. A site that takes more than five seconds to load is at risk of losing both the web user’s attention and a potential sale.
A team of computer scientists at Johns Hopkins University propose a solution for the loading page wait-time in their latest award-winning research, “DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching.” Xin Jin, Assistant Professor and Vladimir Braverman, Associate Professor, along with PhD students Zaoxing Liu and Zhihao Bai, won best paper for their research at the 17th USENIX Conference on File and Storage Technologies (FAST), held February 25-28, 2019 in Boston, MA.
DistCache is a new, distributed caching mechanism that provides provable load balancing for large-scale storage systems. The project is supported by a $500,000 National Science Foundation grant.
“Nowadays, everyone uses online services like Google, Amazon and Facebook for shopping. All of these ecommerce sites build upon large storage systems that are required to maintain a lot of data to serve their customers. The major challenge for these sites is how to build scalable-distributed storage that can provide both a service to billions of users and give them a satisfactory user-experience,” said Jin.
DistCache already has online providers such as Barefoot Networks interested in its services. Barefoot Networks is a computer networking company that designs and produces programmable network switch silicon, systems, and software.
“DistCache is a general solution that can be applied to many storage systems. We demonstrate the benefits of DistCache by providing the design, implementation, and evaluation of the use case for emerging switch-based caching,” said Braverman.
“DistCache is solving the load imbalance issue in the existing storage clusters, and trying to achieve ideal resource utilization for operators and best user experience on fetching data. The goals of it are to help datacenter operators in the industry to handle the largest and most complex workloads in the fast-growing Internet,” said Liu.
Liu graduated from Hopkins in 2018 with his doctoral degree in Computer Science and is currently a postdoc at Carnegie Mellon University and Harvard. Bai is a second-year PhD student in Computer Science at Hopkins.
The team’s research has been selected to be presented in the Best-of-the-Rest session at USENIX’s Annual Technical Conference, held July 10 -12, 2019 in Renton, WA. To learn more about DistCashe, click here.