Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Many state-of-the-art selectivity estimation methods use query feedback to maintain histogram buckets, thereby using the limited memory efficiently. However, they are "reacti...
Distributed stream processing systems (DSPSs) have many important applications such as sensor data analysis, network security, and business intelligence. Failure management is ess...
Xiaohui Gu, Spiros Papadimitriou, Philip S. Yu, Sh...
In this paper, we present a new online failure forecast system to achieve predictive failure management for fault-tolerant data stream processing. Different from previous reactive ...
Xiaohui Gu, Spiros Papadimitriou, Philip S. Yu, Sh...