Joint Optimization for Visual Data Transmission in the Resource Constraint 5G IoT

• Main Authors: Xu Jingce, Zhang Xinsheng, Lu Jianfei
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: E3S Web of Conferences
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/32/e3sconf_posei2021_02014.pdf

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.