(DSLM), a program can be built by linking program modules to form a network through which data passes. The network is speciJed by the program designer using a mixture of pre-coded and custom coded modules. This linkage technique and the capabilities that result from it constitute an approach to programming that is radically diferent from conventional techniques. It can increase the productivity...

Data stream mining has become a research area of some interest in recent years. The key challenge in data stream mining is extracting valuable knowledge in real time from a massive, continuous, dynamic data stream in only a single scan. Clustering is an efficient tool to overcome this problem. Data stream clustering can be applied in various fields such as financial transactions, telephone reco...

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 ...

How does one deal with massive data sets that is available for analyses? We will describe the classical data stream model in which we make one pass over the data and with sublinear resources perform much of the data analyses we care about, such as frequent items, summaries, compressed sensing, clustering and others. We will present the basic algorithmic techniques used to build the sophisticate...

Recent research efforts in the fields of data stream processing and data stream management systems (DSMSs) show the increasing importance of processing data streams, e. g., in the e-science domain. Together with the advent of peer-to-peer (P2P) networks and grid computing, this leads to the necessity of developing new techniques for distributing and processing continuous queries over data strea...

dss (data stream scan) is a framework for describing, transforming, reading, querying, and writing streams of record oriented data. dss is implemented as a command and library API and used extensively to aid network measurements in our organization. The API is extended by DLLs (shared libraries) that define data domain specific I/O, type and query functions. We provide a best-in-class repositor...