Autopipelining for Data Stream Processing

Synchronizing data stream processing

Stream-Processing Point Data

With the fast increasing size of captured 3D models, i.e. from high-resolution laser range scanning devices, it has become more and more important to provide basic point processing methods for large raw point data sets. In this paper we present a novel stream-based point processing framework that orders unorganized raw points along a spatial dimension and processes them sequentially. The major ...

Linked Stream Data Processing

Linked Stream Data has emerged as an effort to represent dynamic, time-dependent data streams following the principles of Linked Data. Given the increasing number of available stream data sources like sensors and social network services, Linked Stream Data allows an easy and seamless integration, not only among heterogenous stream data, but also between streams and Linked Data collections, enab...

In-Stream Data Processing for Tactical Environments

Data dissemination and information management technologies for tactical environments are quickly becoming major areas of research for both military and civilian applications. Critical to the problem is the need for fully distributed information management technologies that are efficient, adaptive and resilient. In this paper, we introduce and discuss a new strategy for tactical data disseminati...

Distributed Resource Allocation for Stream Data Processing

Data streaming applications are becoming more and more common due to the rapid development in the areas such as sensor networks, multimedia streaming, and on-line data mining, etc. These applications are often running in a decentralized, distributed environment. The requirements for processing large volumes of streaming data at real time have posed many great design challenges. It is critical t...