When a user performs a search in social media, the request doesn’t stay within that platform. It calls upon the resources of a data center. “When someone sends a request to a data center, they want an immediate answer—they don’t want to wait,” Zhenlin Wang explains.
We designed upon open-source software and memcached that was adopted by Facebook and Twitter. They modified their approach to adapt to user demand. Our method beats their current practices.
Together with colleagues from Peking University, the University of Rochester, Wayne State University, and Michigan Tech, Wang looked to improve the internal structure,
theory, and algorithm of memory cache to make it more efficient.
This work is an offspring of his 2007 CAREER award.
“Currently, bulky disks store the data and are slow to react. When smaller, in-memory cache is used, the search is much faster,” he adds. “We designed upon open-source software and memcached that was adopted by Facebook and Twitter. They modified their approach to adapt to user demand. Our method beats their current practices,” Wang says.
“Imagine inviting 100 people over to your house for dinner, but only four will fit in your dining room. When we think about data resource management, it’s a similar scenario.”