2017Advances in computational intelligence and robotics book seriesRequires access

Data Streams Processing Techniques Data Streams Processing Techniques

Fatma Mohamed, Rasha M. Ismail, Nagwa Badr, Mohamed F. Tolba

Open publisher page 0 citations

Abstract

Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous data streams, we consider in particular continuous queries which are evaluated continuously as data streams continue to arrive. The answer to a continuous query is produced over time, always reflecting the stream data seen so far. One of the most critical requirements of stream processing is fast processing. So, parallel and distributed processing would be good solutions. This paper gives (1) analysis to the different continuous query processing techniques; (2) a comparative study for the data streams execution environments; and (3) finally, we propose an integrated system for processing data streams based on cloud computing which apply continuous query optimization technique on cloud environment.

About this research paper

What this paper is about

Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous data streams, we consider in particular continuous queries which are evaluated continuously as data streams continue to arrive. The answer to a continuous query is produced over time, always reflecting the stream data seen so far. One of the most critical requirements of stream processing is fast processing. So, parallel and distributed processing would be good solutions. This paper gives (1) analysis to the different continuous query processing techniques; (2) a comparative study for the data streams execution environments; and (3) finally, we propose an integrated system for processing data streams based on cloud computing which apply continuous query optimization technique on cloud environment.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous data streams, we consider in particular continuous queries which are evaluated continuously as data streams continue to arrive. The answer to a continuous query is produced over time, always reflecting the stream data seen so far. One of the most critical requirements of stream processing is fast processing. So, parallel and distributed processing would be good solutions. This paper gives (1) analysis to the different continuous query processing techniques; (2) a comparative study for the data streams execution environments; and (3) finally, we propose an integrated system for processing data streams based on cloud computing which apply continuous query optimization technique on cloud environment.

Key concepts: Data stream mining, Computer science, Stream processing, STREAMS, Cloud computing, Data processing, Data stream, Distributed computing

Related papers

Back to paper searchBrowse research topicsOriginal source
Data Streams Processing Techniques Data Streams Processing Techniques — Research Paper | ScholarLens