The Design and Implementation of a Semi-autonomic Data Stream Query Processing Testbed

2014 ◽  
Author(s):  
Courtney Humphries ◽  
Dawn Wilkins
Keyword(s):  
Query Processing ◽  
Data Stream ◽  
Design And Implementation ◽  
Stream Query Processing

scholarly journals Streaming Video Classification Using Machine Learning

2020 ◽  
Vol 17 (4A) ◽  
pp. 677-682
Author(s):  
Adnan Shaout ◽  
Brennan Crispin
Keyword(s):  
Machine Learning ◽  
Decision Process ◽  
Data Stream ◽  
Streaming Video ◽  
Learning System ◽  
Network Interface ◽  
Video Classification ◽  
Design And Implementation ◽  
Markov Decision ◽  
Streaming Services

This paper presents a method using neural networks and Markov Decision Process (MDP) to identify the source and class of video streaming services. The paper presents the design and implementation of an end-to-end pipeline for training and classifying a machine learning system that can take in packets collected over a network interface and classify the data stream as belonging to one of five streaming video services: You Tube, You Tube TV, Netflix, Amazon Prime, or HBO

XML Stream Query Processing

2010 ◽  
pp. 89-107
Author(s):  
Mingzhu Wei ◽  
Ming Li ◽  
Elke A. Rundensteiner ◽  
Murali Mani ◽  
Hong Su
Keyword(s):  
Query Processing ◽  
Input Data ◽  
Stream Processing ◽  
Query Execution ◽  
Data Semantics ◽  
Stream Query Processing ◽  
Xml Stream ◽  
And Algebra ◽  
Xml Streams ◽  
Compare And Contrast

Stream applications bring the challenge of efficiently processing queries on sequentially accessible XML data streams. In this chapter, the authors study the current techniques and open challenges of XML stream processing. Firstly, they examine the input data semantics in XML streams and introduce the state-of-the-art of XML stream processing. Secondly, they compare and contrast the automatonbased and algebra-based techniques used in XML stream query execution. Thirdly, they study different optimization strategies that have been investigated for XML stream processing – in particular, they discuss cost-based optimization as well as schema-based optimization strategies. Lastly but not least, the authors list several key open challenges in XML stream processing.

Research on Sequence Query Processing Techniques over Data Streams

2013 ◽  
Vol 284-287 ◽  
pp. 3507-3511 ◽  
Author(s):  
Edgar Chia Han Lin
Keyword(s):  
Query Processing ◽  
Data Streams ◽  
Management System ◽  
Data Stream ◽  
Sensor Data ◽  
Data Management System ◽  
Content Filtering ◽  
Data Stream Management ◽  
Stream Management ◽  
Great Progress

Due to the great progress of computer technology and mature development of network, more and more data are generated and distributed through the network, which is called data streams. During the last couple of years, a number of researchers have paid their attention to data stream management, which is different from the conventional database management. At present, the new type of data management system, called data stream management system (DSMS), has become one of the most popular research areas in data engineering field. Lots of research projects have made great progress in this area. Since the current DSMS does not support queries on sequence data, this project will study the issues related to two types of data. First, we will focus on the content filtering on single-attribute streams, such as sensor data. Second, we will focus on multi-attribute streams, such as video films. We will discuss the related issues such as how to build an efficient index for all queries of different streams and the corresponding query processing mechanisms.

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