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CPU Frequency Scaling Optimization in Sustainable Edge Computing

delete2023-04-01
delete3
PRE
AI
Y
Yu Luo
L
Lina Pu
C
Chun‐Hung Liu
DOI:10.1109/TSUSC.2022.3217970delete
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摘要

摘要

En 中文
Sustainable edge computing (SEC) is a promising technology that can reduce energy consumption and computing latency for the mobile Internet of Things (IoT). By collecting renewable energy such as solar or wind energy from the environment, a sustainable cloudlet outside the electric grid can provide powerful computing capabilities for resource-constrained mobile IoT devices. In the real world, the density of sustainable energy can vary significantly over time. Therefore, the SEC cloudlet needs to dynamically adjust the clock frequency to balance energy consumption and computing latency. In this paper, we consider the limited energy storage of the cloudlet and the dynamic intensity of renewable energy, and then develop offline optimal CPU frequency scaling policies that (a) maximize the computing power of the cloudlet within a certain period of time, and (b) minimize the execution time given tasks offloaded to the cloudlet. An optimal tightest string policy is proposed to solve the optimization problem. In addition, a dynamic programming (DP) based suboptimal solution is introduced to simplify the practical implementation. How to design an online CPU frequency management strategy is also briefly discussed.
Keyword:
Cloud computing
Task analysis
Internet of Things
Renewable energy sources
Optimization
Clocks
Servers
Sustainable edge computing (SEC)
cloudlet CPU frequency scaling
energy harvesting
mobile Internet of things (IoT)

期刊

I
IEEE Transactions on Cloud Computing
IF:
5
论文数:
1.9K
被引数:
4.3K

机构

University of Alabama System 封面图
University of Alabama System
学者数:
4.2W
论文数: 3.8W
被引数: 68
M
mississippi state university
学者数:
7.4K
论文数: 6.9K
被引数: 70
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