返回
A Mobile-assisted Edge Computing Framework for Emerging IoT Applications
DOI:10.1145/3461841.png)
摘要
En 中文
Edge computing (EC) is a promising paradigm for providing ultra-low latency experience for IoT applications at the network edge, through pre-caching required services in fixed edge nodes. However, the supply-demand mismatch can arise while meeting the peak period of some specific service requests. The mismatch between capacity provision and user demands can be fatal to the delay-sensitive user requests of emerging IoT applications and will be further exacerbated due to the long service provisioning cycle. To tackle this problem, we propose the mobile-assisted edge computing framework to improve the QoS of fixed edge nodes by exploiting mobile edge nodes. Furthermore, we devise a CRI (Credible, Reciprocal, and Incentive) auction mechanism to stimulate mobile edge nodes to participate in the services for user requests. The advantages of our mobile-assisted edge computing framework include higher task completion rate, profit maximization, and computational efficiency. Meanwhile, the theoretical analysis and experimental results guarantee the desirable economic properties ofour CRI auction mechanism.
Keyword:
The supply-demand mismatch
mobile-assisted edge computing
emerging IoT applications
mechanism design
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.7
论文数:
1.0K
被引数:
2.0K
机构
引用论文
A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms: Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet端边云编排网络计算范例调查: 透明计算、移动边缘计算、雾计算和Cloudlet
Highly selective and sensitive colorimetric chemosensor for detection of Co2+ in a near-perfect aqueous solution
RSC Advances
IF0
Deep Reinforcement Learning for Cooperative Content Caching in Vehicular Edge Computing and Networks

