Per-flow size measurement is key to many streaming applications and management
systems, particularly in high-speed networks. Performing such measurement on the data …

Active elephant flows, which indicate the real-time data transmission status, are of primary
interest in network management and various applications. However, existing network …

Finding top-K frequent items has been a hot topic in data stream processing in recent years,
which has a wide range of applications. However, most of existing sketch algorithms focuses …

Accurate and fast data stream mining is critical and fundamental to many tasks, including
time series database handling, big data management and machine learning. Different heavy …

Network measurement probes the underlying network to support upper-level decisions such
as network management, network update, network maintenance, network defense and …

Inner-product estimation is the base of many important tasks in a variety of big data
scenarios, including measuring similarity of streams in data stream processing, estimating …

The bumps and dips in data streams are valuable patterns for data mining and networking
scenarios such as online advertising and botnet detection. In this paper, we define the wave …

In large data streams consisting of sequences of data items, those appearing over a long
period of time are regarded as persistent. Compared with frequent items, persistent items do …

To estimate item frequencies of data streams with limited space, sketches are widely used in
real applications, including real-time web analytics, network monitoring, and self-driving …

High-accuracy real-time data stream estimations are critical for various applications, and
sliding-window-based techniques have attracted wide attention. However, existing solutions …