Equipment manufacturers research and development CaptureVuTM technology allows rapid isolation and debugging of equipment and system faults Multiplexer/remultiplexer allows flexible test stream creation and modification Rapid and in-depth analysis of selected elements of transport streams to confirm functionality and compliance to standards Set-top box buffer testing and verification Elementary...

An Internet Protocol/Generic Stream Encapsulation (IP/GSE) signalling framework is proposed to replace the current MPEG-2 Transport Stream (TS) Table-based signalling system and to enable smoother convergence of Digital Video Broadcasting (DVB) transmission systems and IP networks. GSE suitability is explained and a review of IP-based signalling techniques is presented in order to select the op...

Stream Processing Applications analyze large volumes of streaming data in real-time. These applications, consist of data sources, which produce raw streams, and processing elements, which operate on the streams to produce new derived streams. In this paper, we describe an OWL-based model for describing these stream processing components. The streams produced by data sources are described as RDF...

Mining data streams has been a focal point of research interest over the past decade. Hardware and software advances have contributed to the significance of this area of research by introducing faster than ever data generation. This rapidly generated data has been termed as data streams. Credit card transactions, Google searches, phone calls in a city, and many others\are typical data streams. ...

Data stream processing systems are used to continuously run mission-critical applications for real-time monitoring and alerting. These require high throughput low latency process incoming data streams in real time. However, changes the distribution of over time can cause partition skew, which is defined as an unequal partitions among workers, resulting sub-optimal due unbalanced load. This pape...

The events generated by such an active database could be used by themselves, but it is much more interesting if they can be reuse as primitive events for more complex events. For example combining events from multiple active databases and also other sources. This implies that we do the event detection in the network, or have a way of getting notified every time when an interesting event occurs ...

Online, one-pass mining Web click streams poses some interesting computational issues, such as unbounded length of streaming data, possibly very fast arrival rate, and just one scan over previously arrived Web click-sequences. In this paper, we propose a new, single-pass algorithm, called DSM-TKP (Data Stream Mining for Top-K Path traversal patterns), for mining a set of top-k path traversal pa...

Much of the research regarding streaming data has focused only on real time querying and analysis of recent data stream allowable in memory. However, as data stream mining, or tracking of past data streams, is often required, it becomes necessary to store large volumes of streaming data in stable storage. Moreover, as stable storage has restricted capacity, past data stream must be summarized. ...

Distributed Stream Processing frameworks are being commonly used with the evolution of Internet of Things(IoT). These frameworks are designed to adapt to the dynamic input message rate by scaling in/out.Apache Storm, originally developed by Twitter is a widely used stream processing engine while others includes Flink [8] Spark streaming [73]. For running the streaming applications successfully ...