Processing Sampled Big Data

Big Data Processing: Big Challenges and Opportunities

With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as...

In-Stream Big Data Processing

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that realtime query processing and in-stream processing is the immediate need in many practical applications. In recent years, this idea got a lot of traction and a whole bunch of solutions like Twitter’s Storm, Yahoo’s S4, Cloudera’s Impala, A...

Error-Tolerant Big Data Processing

Real-world data contains various kinds of errors. Before analyzing data, one usually needs to process the raw data. However, traditional data processing based on exactly match often misses lots of valid information. To get high-quality analysis results and fit in the big data era, this thesis studies the error-tolerant big data processing. As most of the data in real world can be represented as...

Structural Properties of Multirate Sampled-Data Systems

The application of Networked Control Systems (NCS) in which sensory and control signals are transmitted via shared data communication networks, is growing significantly and these systems have been the subject of research during the last decade. On the other hand, multirate sampled data systems have been investigated since a long time. In this paper, conditions under which a networked control sy...

Distributed Processing for Big Data Video Analytics