A lot of real-time database (RTDB) research has been done to process transactions in a timely fashion using fresh data reflecting the current real world status. However, most existing RTDB work is based on simulations. Due to the absence of a publicly available RTDB testbed, it is very hard to evaluate real-time data management techniques in a realistic environment. To address the problem, we design and develop an initial version of a RTDB testbed, called RTDB2 (Real-Time Database Benchmark), atop an open source database [5]. We develop soft real-time database workloads that model online stock trades, providing several knobs to specify workloads for RTDB performance evaluation. In addition, we develop a QoS management scheme in RTDB2 to detect overload and reduce workloads, via admission control and adaptive temporal data updates, under overload. From the extensive experiments using the stock trading workloads developed in RTDB2, we observe that adaptive updates can considerably impr...
Kyoung-Don Kang, Phillip H. Sin, Jisu Oh