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TaskAlloc: Online Tasks Allocation for Offloading in Energy Harvesting Mobile Edge Computing

delete2019-12-01
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PRE
AI
J
Jiang, Qiucen *
S
Songtao Guo
Y
Yifan Dong
Q
Quyuan Wang
DOI:10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00027delete
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摘要

摘要

En 中文
MEC (Mobile Edge Computing) is a new mobile computation technology which can greatly reduce the execution latency of tasks as well as energy consumption by offloading the computing workload generated by mobile devices to MEC servers. However, due to limited battery capacity of mobile devices, the computing tasks might be abandoned. In this paper, we present an efficient strategy of tasks allocation in an MEC system with energy harvesting to minimize the weight-sum of computation delay and energy cost for mobile devices. In addition, we design a queue for the coming tasks from which the devices fetch the tasks to execute. Based on the Lyapunov optimization method, an online algorithm named Dynamic Lyapunov Optimization-based Tasks Allocation (DLOTA) is presented , to determine the strategy by adjusting both the CPU frequency and the offloading transmission power of mobile devices. Its advantage is that the tasks allocation decision only depends on the state of the current system and does not need to predict the future state. Simulation results demonstrate that the presented method can make the battery energy levels stable and achieve the trade off between execution delay and energy cost.
Keyword:
Mobile edge computing
Lyapunov optimization
Task allocation
Execution delay
Energy harvesting
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期刊

I
IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking
IF:
0
论文数:
4
被引数:
0

机构

S
southwest university - china
学者数:
2.6W
论文数: 1.9W
被引数: 21
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