DocumentCode :
2846178
Title :
Resource Allocation for Distributed Streaming Applications
Author :
Zhu, Qian ; Agrawal, Gagan
Author_Institution :
Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH
fYear :
2008
fDate :
9-12 Sept. 2008
Firstpage :
414
Lastpage :
421
Abstract :
We consider resource allocation for distributed streaming applications running in a grid environment, where continuously streaming data needs to be aggregated and processed to produce output streams. Because such an application comprises a pipeline of processing stages, both communication and computational requirements need to be taken into account while performing resource allocation. In this paper, we give a rigorous formulation of this resource allocation problem, based on the DAG representation of the application as well as the environment. We have shown how we can use the notion of subgraph isomorphism and developed an effective resource allocation algorithm. The main observations from the experiments we conducted to evaluate our algorithms were as follows: the overhead caused by our algorithm is comparable to an existing algorithm, Streamline, which is based onheuristics. At the same time, the application performance was improved by 30% on average. When compared to the allocation performed by the optimal algorithm, which enumerates all mappings, the application performance with our algorithm was within 4%. At the same time, unlike the optimal algorithm, our algorithm scaled well to large graphs.
Keywords :
graph theory; grid computing; pipeline processing; resource allocation; DAG representation; data streaming; distributed streaming applications; optimal algorithm; resource allocation algorithm; subgraph isomorphism; Application software; Bandwidth; Computer science; Data engineering; Data processing; Image sensors; Medical simulation; Parallel processing; Pipelines; Resource management; Data Streaming Applications; Grid Computing; Resource Allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing, 2008. ICPP '08. 37th International Conference on
Conference_Location :
Portland, OR
ISSN :
0190-3918
Print_ISBN :
978-0-7695-3374-2
Electronic_ISBN :
0190-3918
Type :
conf
DOI :
10.1109/ICPP.2008.49
Filename :
4625876
Link To Document :
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