Joint Long-Term Energy Efficiency Optimization for Energy Harvesting-Enabled Mobile Edge Computing

被引：1
|
作者：
Zhang, Songlei [1 ]
Chen, Xiaoqian [1 ]
Ma, Chao [1 ]
Hua, Meihui [1 ]
Tian, Hui [1 ]
Nie, Gaofeng [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beiing Smartchip Microelectron Technol Co Ltd, State Grid Fujian Informat Telecommunicat Co, Beijing, Peoples R China
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON SATELLITE COMPUTING, SATELLITE | 2022年
关键词：
D O I：
10.1109/Satellite55519.2022.00022
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, an energy harvesting-enabled mobile edge computing system is investigated. We formulate a longterm energy efficiency (EE) maximization problem under the constraints of network stability. Based on the Lyapunov optimization and fractional programming frameworks, an online resource allocation algorithm is proposed to jointly optimizing task partition, CPU frequency, power allocation and energy harvesting strategy at MDs. Simulation results demonstrate the performance advantage of EH-enabled MEC.
引用
收藏
页码：58 / 59
页数：2
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