Abstract
We present Asterism, an open source data-intensive framework, which combines the strengths of traditional work-flow management systems with new parallel stream-based data flow systems to run data-intensive applications across
multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment engines; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods
with computing resources; and store and transfer large/small volumes of data. We also present the Data-Intensive work-flows as a Service (DIaaS) model, which enables easy dataintensive work flow composition and deployment on clouds using containers. The feasibility of Asterism and DIaaS model have been evaluated using a real domain application on the NSF-Chameleon cloud. Experimental results shows how Asterism successfully and eciently exploits combinations of diverse computational platforms, whereas DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust way reducing the engineering time and computational cost.
multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment engines; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods
with computing resources; and store and transfer large/small volumes of data. We also present the Data-Intensive work-flows as a Service (DIaaS) model, which enables easy dataintensive work flow composition and deployment on clouds using containers. The feasibility of Asterism and DIaaS model have been evaluated using a real domain application on the NSF-Chameleon cloud. Experimental results shows how Asterism successfully and eciently exploits combinations of diverse computational platforms, whereas DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust way reducing the engineering time and computational cost.
| Original language | English |
|---|---|
| Title of host publication | DataCloud '16 Proceedings of the 7th International Workshop on Data-Intensive Computing in the Cloud |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 1-8 |
| Number of pages | 8 |
| ISBN (Print) | 978-1-5090-6158-7 |
| DOIs | |
| Publication status | Published - 13 Nov 2016 |
| Event | 7th International Workshop on Data-Intensive Computing in the Cloud - Salt Lake City, United States Duration: 13 Nov 2016 → 18 Nov 2016 http://sc16.supercomputing.org/ |
Conference
| Conference | 7th International Workshop on Data-Intensive Computing in the Cloud |
|---|---|
| Abbreviated title | SC16 |
| Country/Territory | United States |
| City | Salt Lake City |
| Period | 13/11/16 → 18/11/16 |
| Internet address |