摘要
面对时延敏感度不同的多种用户,如何有效利用频谱资源和计算资源受限的边缘节点来保障其时延能耗需求成为关键问题。为此,提出了基于移动边缘计算(mobile edge computing,MEC)的任务卸载和资源分配联合优化方案。首先,为最小化卸载任务在MEC的总计算时间,给每个用户分配最优的MEC计算资源。其次,基于时延敏感度、用户满意度和资源块(resource block,RB)质量,引入RB分配算法,以分布式执行。最后,用户通过比较本地计算开销和卸载计算开销做出卸载决策。仿真结果表明,所提算法在满足高时延敏感用户的需求前提下,通过有效地分配传输资源和计算资源,实现了最小的系统开销。
Faced with multiple users with different delay sensitivities,how to effectively use transmission resources and computing resources in limited edge nodes to ensure the delay and energy requirements of users becomes a key issue.To this end,ajoint optimization scheme based on mobile edge computing(MEC)for task offloading and resource allocation is proposed.Firstly,to minimize the total computation time of the offloading tasks at MEC,each user is assigned with the optimal MEC computing resource.Secondly,a resource block(RB)distribution algorithm based on the delay-sensitive,satisfaction degree and quality of RBs is introduced in a distributed manner.Finally,each user makes the offloading decision by comparing the local computational overhead with the offloading computational overhead.The simulation results show that the proposed algorithm achieves the minimum system overhead by effectively allocating transmission resources and computing resources under the premise of meeting the requirements of high-latency sensitive users.
作者
黄晓舸
崔艺凡
张东宇
陈前斌
HUANG Xiaoge;CUI Yifan;ZHANG Dongyu;CHEN Qianbin(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2020年第6期1386-1394,共9页
Systems Engineering and Electronics
基金
国家自然科学基金重点项目(61831002)
重庆市科委重庆市基础研究与前沿探索项目(cstc2018jcyjAx0383)资助课题。
关键词
资源分配
移动边缘计算
时延敏感度
卸载决策
resource allocation
mobile edge computing(MEC)
delay-sensitive
offloading decision
