An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications
In this paper, we propose a novel efficient dataflow execution method for mobile context monitoring applications. As a key approach to minimize the execution overhead, we propose a new dataflow execution model, producer-oriented model. Compared to the conventional consumer-oriented model adopted in...
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sg-smu-ink.sis_research-30682016-11-08T08:03:47Z An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications JU, Younghyun MIN, Chulhong LEE, Youngki YU, Jihyun SONG, Junehwa In this paper, we propose a novel efficient dataflow execution method for mobile context monitoring applications. As a key approach to minimize the execution overhead, we propose a new dataflow execution model, producer-oriented model. Compared to the conventional consumer-oriented model adopted in stream processing engines, our model significantly reduces execution overhead to process context monitoring dataflow reflecting unique characteristics of context monitoring. To realize the model, we develop DataBank, an execution container that takes charge of the management and delivery of the output data for the associated operator. We demonstrate the effectiveness of DataBank by implementing three useful applications and their dataflow graphs, i.e., MusicMap, FindMyPhone, and CalorieMonitor. Using the applications, we show that DataBank reduces the CPU utilization by more than 50%, compared to the methods based on the consumer-oriented model; DataBank enables more context monitoring applications to run concurrently. 2012-03-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/2069 info:doi/10.1109/PerCom.2012.6199857 http://dx.doi.org/10.1109/PerCom.2012.6199857 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Context monitoring Dataflow execution Performance Computer Sciences Software Engineering |
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Context monitoring Dataflow execution Performance Computer Sciences Software Engineering JU, Younghyun MIN, Chulhong LEE, Youngki YU, Jihyun SONG, Junehwa An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
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In this paper, we propose a novel efficient dataflow execution method for mobile context monitoring applications. As a key approach to minimize the execution overhead, we propose a new dataflow execution model, producer-oriented model. Compared to the conventional consumer-oriented model adopted in stream processing engines, our model significantly reduces execution overhead to process context monitoring dataflow reflecting unique characteristics of context monitoring. To realize the model, we develop DataBank, an execution container that takes charge of the management and delivery of the output data for the associated operator. We demonstrate the effectiveness of DataBank by implementing three useful applications and their dataflow graphs, i.e., MusicMap, FindMyPhone, and CalorieMonitor. Using the applications, we show that DataBank reduces the CPU utilization by more than 50%, compared to the methods based on the consumer-oriented model; DataBank enables more context monitoring applications to run concurrently. |
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text |
author |
JU, Younghyun MIN, Chulhong LEE, Youngki YU, Jihyun SONG, Junehwa |
author_facet |
JU, Younghyun MIN, Chulhong LEE, Youngki YU, Jihyun SONG, Junehwa |
author_sort |
JU, Younghyun |
title |
An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
title_short |
An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
title_full |
An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
title_fullStr |
An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
title_full_unstemmed |
An Efficient Dataflow Execution Method for Mobile Context Monitoring Applications |
title_sort |
efficient dataflow execution method for mobile context monitoring applications |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2012 |
url |
https://ink.library.smu.edu.sg/sis_research/2069 http://dx.doi.org/10.1109/PerCom.2012.6199857 |
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1770571784055160832 |