.png){kind=icon}
返回
Joint Task Offloading and Resource Allocation for Energy-Constrained Mobile Edge Computing
.png){kind=icon}
PRE
AI
DOI：10.1109/TMC.2022.3150432.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We consider the problem of task offloading and resource allocation in mobile edge computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile devices (MDs) may offload their tasks to edge servers based on the allocated computation (e.g., CPU/GPU cycles and storage) and wireless resources (e.g., bandwidth). However, these resources could not be effectively utilized unless an encouraging resource allocation scheme can be proposed. What's worse, task offloading incurs additional MEC energy consumption, which inevitably violate the long-term MEC energy budget. Considering these two challenges, we propose an online joint offloading and resource allocation (JORA) framework under the long-term MEC energy constraint, aiming at guaranteeing the end-users' QoE. To achieve this, we leverage Lyapunov optimization to exploit the optimality of the long-term QoE maximization problem. By constructing an energy deficit queue to guide energy consumption, the problem can be solved in a real-time manner. On this basis, we propose online JORA methods in both centralized and distributed manners. Furthermore, we prove that our proposed methods enable the achievement of the close-to-optimal performance while satisfying the long-term MEC energy constraint. In addition, we conduct extensive simulations and the results show superiority in performance over other methods.
Keyword:
Task analysis
Servers
Resource management
Bandwidth
Quality of experience
Energy consumption
Delays
Task offloading
mobile edge computing
energy-constrained edge
Lyapunov optimization
game theory
期刊
IF:
9.2
论文数:
5.6K
被引数:
1.8W
机构
引用论文
Regulation and Functions of the lms Homeobox Gene during Development of Embryonic Lateral Transverse Muscles and Direct Flight Muscles in Drosophila.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏分享收藏Joint Data Collection and Resource Allocation for Distributed Machine Learning at the Edge边缘分布式机器学习的联合数据收集和资源分配
PREAI
分享收藏Measuring AIDS stigmas in people living with HIV/AIDS: the Internalized AIDS-Related Stigma ScaleAIDS Care
AIDS CareIF0
PREAI
分享收藏Wearable Sensor Devices for Prevention and Rehabilitation in Healthcare: Swimming Exercise With Real-Time Therapist Feedback用于医疗保健预防和康复的可穿戴传感器设备: 具有实时治疗师反馈的游泳运动
PREAI
分享收藏
查看更多内容