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A design proto‐pattern for continuously evaluated forecasting in IBM® InfoSphere® Streams

“…By disseminating known good solutions, design patterns expedite software development and increase maintainability. While development of streaming applications is greatly simplified by the Streams platform, end-to-end solutions remain challenging to develop, as Turaga et al [4] explain, 'These characteristics [of streaming applications] require a shift in the developer thought process and the engineering methods employed during the application design, development, and evolution.' We offer our proto-pattern to further simplify, and expedite, the development of applications in Streams for multistep forecasting over any suitable data stream.…”

“…Stream computing answers the growing need to process an increasing extent of connectivity between an increasing number of heterogeneous data sources [5]. Stream computing applications continually receive signals from external sources and analyze them for actionable information [4].…”

“…If multiple hosts had been available, we would have used placement [13]. With only one host available, the data volume was instead reduced by sampling [4]. A sampling rate of one tuple in 60 was selected.…”

“…• If sampling [4] is applied, archive completeness could be maintained with fusion and placement [13]. • Compare accuracy of multiple forecasts.…”

Skeleton Paradigm for Developing E-Science Applications on Distributed Platforms

“…This high-level parallel programming technique enables to develop programs by composing a set of skeletons. The programmer adheres to top-down design and construction where the control is inherited through the structure [1]. The skeleton proposes a set of interfaces to end-users allowing them to design their computational parallel applications.…”