ACDS: Adapting computational data streams for high performance
- 7 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Data-intensive, interactive applications are an important class of metacomputing (Grid) applications. They are characterized by large, time-varying data flows between data providers and consumers. The topic of this paper is the runtime adaptation of data streams, in response to changes in resource availability and/or in end user requirements, with the goal of continually providing to consumers data at the levels of quality they require. Our approach is one that associates computational objects with data streams. Runtime adaptation is achieved by adjusting objects' actions on streams, by splitting and merging objects, and by migrating them (and the streams on which they operate) across machines and network links. Adaptive streams also react to changes in resource availability detected by online monitoring.Keywords
This publication has 7 references indexed in Scilit:
- Steering data streams in distributed computational laboratoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- ILI: an adaptive infrastructure for dynamic interactive distributed applicationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- An object-based infrastructure for program monitoring and steeringPublished by Association for Computing Machinery (ACM) ,1998
- Globus: a Metacomputing Infrastructure ToolkitThe International Journal of Supercomputer Applications and High Performance Computing, 1997
- A parallel spectral model for atmospheric transport processesConcurrency: Practice and Experience, 1996
- Legion-a view from 50,000 feetPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1996
- Dynamic adaptation of real-time softwareACM Transactions on Computer Systems, 1991