The research kernel is to design an effective single data set scanning arithmetic,update synopsis data structure which represents the data set in the memory space that less than data scale continually,then draw an approximate query result quickly according to this struct.

First,the synopsis data structure of data streams is constructed by concise sampling method.

The ways to devise such synopsis data structures are introduced.

A new hierarchical sketch data structure was implemented,which summarized the hierarchical structure in stream data and the key component of which was a pairwise independent family of hash functions based on exclusive-or operator.

A hierarchical Count-Min(HCM) sketch data structure is implemented to summarize the hierarchical structure in stream data.

The main contributions included: the sketch data structure and the frequent sketch algorithm of data streams were designed for anomaly detection of LSN.

In this paper,an anomaly detection method is proposed based on the summary data structure—sketch.

It projects the key network traffic information into summary data structure(sketch)in every circle online which is used to detect anomalies.

Discrete wavelet transform is often used in construction of synopses for streaming data.