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Correlation-Based Device Energy-Efficient Dynamic Multi-Task Offloading for Mobile Edge Computing
DOI:10.1109/VTC2021-Spring51267.2021.9448864.png)
摘要
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Task offloading to mobile edge computing (MEC) has emerged as a key technology to alleviate the computation workloads of mobile devices and decrease service latency for the computation-intensive applications. Device battery consumption is one of the limiting factors needs to be considered during task offloading. In this paper, multi-task offloading strategies have been investigated to improve device energy efficiency. Correlations among tasks in time domain as well as task domain are proposed to be employed to reduce the number of tasks to be transmitted to MEC. Furthermore, a binary decision tree based algorithm is investigated to jointly optimize the mobile device clock frequency, transmission power, structure and number of tasks to be transmitted. MATLAB based simulation is employed to demonstrate the performance of our proposed algorithm. It is observed that the proposed dynamic multi-task offloading strategies can reduce the total energy consumption at device along various transmit power versus noise power point compared with the conventional one.
Keyword:
Task offloading
device energy efficiency
MEC
correlation
task splitting
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Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks5g异构网络中面向移动边缘计算的高能效卸载
IEEE ACCESS
IF3.6
Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications移动边缘计算中用于超可靠低延迟通信的卸载方案
IEEE ACCESS
IF3.6
Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing面向超可靠低延迟边缘计算的动态任务分流和资源分配
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