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Energy-Efficient Task Offloading for Time-Sensitive Applications in Fog Computing

delete2019-09-01
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PRE
AI
Y
Yu-Lin Jiang
Y
Ya-Shu Chen *
S
Su-Wei Yang
C
Chia-Hsueh Wu
DOI:10.1109/JSYST.2018.2877850delete
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摘要

摘要

En 中文
Fog computing has attracted considerable attention to meet the location awareness and real-time response requirements of various applications. However, compared to cloud computing, fog devices have relatively limited power supplies, computation resources, and communication resources, raising design challenges to meet real-time response requirements. To balance response time and energy consumption for multiple fog devices running multiple applications, this work presents an energy-efficient offloading decision mechanism and an offloading dispatcher to dispatch applications to the corresponding device by effectively managing the computation and communication resources of all devices in a fog computing environment. The offloading tasks are composed of several subtasks with an end-to-end deadline. To meet the response time requirements of such applications, a run-time scheduler with an end-to-end latency schedulability consideration is also presented. Evaluation results show considerable energy savings using this framework and a real platform study provides validation.
Keyword:
Energy efficiency
fog computing
Internet of Things
offloading
AI总结

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期刊

I
IEEE Open Journal of Circuits and Systems
IF:
2.4
论文数:
4.5K
被引数:
387

机构

N
national taiwan university of science & technology
学者数:
8.8K
论文数: 8.7K
被引数: 9
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