首页    期刊浏览 2024年07月08日 星期一
登录注册

文章基本信息

  • 标题:Joint Optimization for Visual Data Transmission in the Resource Constraint 5G IoT
  • 本地全文:下载
  • 作者:Jingce Xu ; Xinsheng Zhang ; Jianfei Lu
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:256
  • 页码:1-7
  • DOI:10.1051/e3sconf/202125602014
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:With the integration of 5G and Internet of Things (IoT), the application of large-scale IoT devices networking is increasingly extensive, such as building management, property maintenance, autonomous vehicles, healthcare, and shopping to tourism. In these scenes, the volume of data transmission is quite large, especially visual data (image, video, et al). However, due to the limited resource of IoT devices, such as battery, power, bandwidth, visual data transmission is complex to optimize, single objective optimization is difficult to insure the optimal latency, throughput and power at the same time. In this paper, we propose a method to jointly optimize the resource allocation of visual data transmission in resource constraint 5G IoT. Instead of single objective optimization, we combine the bandwidth, power consumption and latency into a hybrid model, then propose a low-complexity algorithm to solve this multiple objective optimization problem. The simulation results demonstrate that the proposed method increases the comprehensive utility of visual data transmission in the resource constraint 5G-IoT by 35%-48% compared with existing approaches.
国家哲学社会科学文献中心版权所有