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

Finding top-frequent items has been a hot topic in data stream processing with wide-ranging
applications. However, most existing sketch algorithms focus on finding local top-in a single …

Graph stream is a special kind of data stream, where every item coming in sequence
represents an edge in a dynamic graph. Graph stream has wide application in many fields …

Data stream processing holds great potential value in lots of practical application scenarios.
This paper studies two new but important patterns for items in data streams, called promising …

In network measurement, sliding window measurement has the advantage of providing
recent and timely measurement results. Recently, sketches have become the most popular …

In quantile estimation within a stream of key-value pairs, recent work has made significant
progress in query flexibility, supporting quantile estimation for any key using a unified …

Sketch algorithms are crucial for identifying top-k items in large-scale data streams. Existing
methods often compromise between performance and accuracy, unable to efficiently handle …

In today's data–driven world, the explosive growth of network traffic often leads to network
congestion, which seriously affects service performance and user experience. Network traffic …

As the emergence of recently popular large language model, distributed training (DT)
optimizes the performance via using different parallelization strategies, resource schedulers …

In many applications, data streams are indispensable to describe the relationships between
nodes in networks, such as social networks, computer networks, and hyperlink networks …