Abstract | ||
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Stream processing systems have evolved into established solutions as standalone engines but they still lack flexibility in terms of large-scale deployment, integration, extensibility, and interoperability. In the last years, a substantial ecosystem of new applications has emerged that can potentially benefit from stream processing but introduces different requirements on how stream processing solutions can be integrated, deployed, extended, and federated. To address these needs, we present an exoengine architecture and the associated ExoP platform. Together, they provide the means for encapsulating components of stream processing systems as well as automating the data exchange between components and their distributed deployment. The proposed solution can be used, e.g., to connect heterogeneous streaming engines, replace operators at runtime, and migrate operators across machines with a negligible overhead. |
Year | DOI | Venue |
---|---|---|
2011 | 10.1007/978-3-642-25821-3_14 | Middleware |
Keywords | Field | DocType |
virtualizing stream processing,stream processing system,stream processing,large-scale deployment,different requirement,exoengine architecture,encapsulating component,exop platform,stream processing solution,established solution,data exchange,virtualization | Virtualization,Architecture,Data exchange,Software deployment,Interoperability,Computer science,Operator (computer programming),Stream processing,Extensibility,Distributed computing | Conference |
Volume | ISSN | Citations |
7049 | 0302-9743 | 5 |
PageRank | References | Authors |
0.52 | 26 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Michael Duller | 1 | 44 | 6.16 |
Jan S. Rellermeyer | 2 | 280 | 20.20 |
Gustavo Alonso | 3 | 5476 | 612.79 |
Nesime Tatbul | 4 | 3415 | 239.74 |