计算机科学
利润(经济学)
基站
移动边缘计算
服务质量
前进飞机
能源消耗
服务器
服务提供商
粒子群优化
接入网
计算机网络
数学优化
算法
服务(商务)
数学
网络数据包
经济
微观经济学
经济
生物
生态学
作者
Yuanzhe Li,Ao Zhou,Xiao Ma,Shangguang Wang
标识
DOI:10.1109/jiot.2021.3082898
摘要
In a 5G network, mobile-edge computing (MEC) plays a key role in providing low access delay services. The placement of edge servers not only determines the quality of services on the user side but also affects the profit of running a MEC system. In this article, we study how to properly place edge servers so as to guarantee the access delay and maximize the profit of edge providers. We first propose a profit model which involves both access delay and energy consumption. In this model, we take the 5G user plane function (UPF) into consideration to calculate access delay for the first time. Then, we devise a particle swarm optimization-based algorithm to optimize the profit. In the algorithm, we introduce a weight value $q$ to guarantee the access delay and assign base stations properly. Moreover, a service-level agreement is adopted to balance the tradeoff between access delay and energy consumption. We take advantage of our 5G network emulator called mini5Gedge and data set from Shanghai Telecom to conduct massive experiments. The results show that our algorithm stands out in terms of achieving the highest profit.
科研通智能强力驱动
Strongly Powered by AbleSci AI