.png){kind=icon}
返回
Energy-Efficient Computation Offloading in Mobile Edge Computing Systems With Uncertainties
.png){kind=icon}
OA
AI
DOI：10.1109/TWC.2022.3142685.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Computation offloading is indispensable for mobile edge computing (MEC). It uses edge resources to enable intensive computations and save energy for resource-constrained devices. Existing works generally impose strong assumptions on radio channels and network queue sizes. However, practical MEC systems are subject to various uncertainties rendering these assumptions impractical. In this paper, we investigate the energy-efficient computation offloading problem by relaxing those common assumptions and considering intrinsic uncertainties in the network. Specifically, we minimize the worst-case expected energy consumption of a local device when executing a time-critical application modeled as a directed acyclic graph. We employ the extreme value theory to bound the occurrence probability of uncertain events. To solve the formulated problem, we develop an c-bounded approximation algorithm based on column generation. The proposed algorithm can efficiently identify a feasible solution that is less than (1 + epsilon) of the optimal one. We implement the proposed scheme on an Android smartphone and conduct extensive experiments using a real-world application. Experiment results corroborate that it will lead to lower energy consumption for the client device by considering the intrinsic uncertainties during computation offloading. The proposed computation offloading scheme also significantly outperforms other schemes in terms of energy saving.
Keyword:
Mobile edge computing
computation offloading
network uncertainties
energy efficiency
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
机构
引用论文
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.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容