.png){kind=icon}
返回
DECO: A Deadline-Aware and Energy-Efficient Algorithm for Task Offloading in Mobile Edge Computing
.png){kind=icon}
PRE
AI
DOI：10.1109/JSYST.2022.3185011.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
With the rapid development in the area of Internet of Things (IoT), the number of delay-sensitive and power-hungry IoT applications has drastically increased over the past few years. Mobile edge computing (MEC) has become an effective computing model for meeting the IoT applications' requirements. However, the resource-constrained nature of the IoT devices, different characteristics of IoT tasks such as delay sensitivity, and heterogeneity of the edge cloud servers (ECSs) make the task offloading problem a fundamental challenge in the MEC systems. Motivated by this, in this article, we propose a deadline-aware and energy-efficient computation offloading algorithm, DECO, for scheduling and processing the generated tasks from the IoT devices. The proposed algorithm jointly takes into account the deadline requirement of the tasks and the energy consumption of the IoT devices in the local decision-making process. Also, it considers the priority of the tasks and heterogeneity of ECSs for the task-node mapping process. The extensive simulation results confirm that the proposed algorithm improves the deadline satisfaction ratio of delay-sensitive tasks about 85.4% and reduces their average response time up to 62.9% compared to the state-of-the-art method while the amount of increase in the total energy consumption of IoT devices is less than 13.4%.
Keyword:
Task analysis
Internet of Things
Delays
Energy consumption
Time factors
Servers
Real-time systems
Deadline-aware
energy-efficient
Internet of Things (IoT)
mobile edge computing (MEC)
task offloading
期刊
I
IF:
2.4
论文数:
4.5K
被引数:
387
机构
引用论文
Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things
PREAI
分享收藏Multi-Objective Whale Optimization Algorithm for Computation Offloading Optimization in Mobile Edge Computing移动边缘计算中计算卸载优化的多目标鲸鱼优化算法.png)
SENSORS
OAAI
SENSORSIF3.5
OAAI分享收藏Detour: Dynamic Task Offloading in Software-Defined Fog for IoT ApplicationsDetour: 物联网应用软件定义雾中的动态任务卸载
PREAI
分享收藏Deep Reinforcement Learning for Energy-Efficient Computation Offloading in Mobile-Edge Computing面向移动边缘计算节能计算卸载的深度强化学习
PREAI
分享收藏
查看更多内容