基于智能电网边缘智能网关的5G流媒体架构

Chao Ma, Xianchun Wang, Rui Xin, Chenjun Sun, Xiaolong Yang, Tian He, Tao Yao
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引用次数: 2

摘要

通过精心编排的5G网络,智能电网与先进的信息通信技术融合,最大限度地减少电力系统事故,提供智能化、规模化的电力管理。在这项工作中,我们提出了一种基于5G网络的具有智能边缘的新型流媒体架构,以满足差异化的QoS需求。我们提出的设计跨越了一个模块化的监控系统架构,包括点对多点MEC网关(MEC- gw)、云媒体服务器、5G网络。该系统利用在边缘GW获取的本地数据,以协同优化的方式控制多点视频流的接入,缓解特定基站附近的交通拥堵。MEC-GW调度器具有先进的适配器属性,可以根据不同的QoS需求调整优先级状态,提高5G接入网的效率。在严格的带宽和Qos约束下,制定5G MEC-GWs联合部署和资源分配优化策略,实现系统能效最大化。通过引入Charnes-Cooper变换,提出了一种非凸松弛优化方法来获得最优解。实际测量和仿真结果表明,该策略具有可扩展性和鲁棒性,并为现有方法提供了补充和节能的改进空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
5G Enabling Streaming Media Architecture with Edge Intelligence Gateway in Smart Grids
Smart Grids is now blending with sophisticated information and communications technology by virtue of orchestrated 5G network to potentially minimize power system accident and provide intelligent and large-scale power management. In this work, we propose a novel streaming media architecture over 5G network with intelligent edge for differentiated QoS requirements. Our proposed design spans a modular surveillance system architecture including the point-to-multipoint MEC gateway (MEC-GW), cloud media server, 5G network. The proposed system leverages the local data acquired at the edge GW to control multipoint video streams access in synergic optimization way, and alleviate traffic congestion near a specific base station (BS). MEC-GW schedulers with advanced adapter properties can adjust the priority state for differentiated QoS requirements and improve the efficiency in the 5G access network. Moreover, the joint 5G MEC-GWs deployment and resource allocation optimization strategy was formulated to maximize system energy efficiency (EE) taking stringent bandwidth and Qos constraints into account. By introducing Charnes-Cooper transform, a non-convex relaxation optimization is proposed to obtain the optimal solution. Real measurement and simulation results show that proposed strategy is scalable and robust, and also offer supplementary and energy-efficient room for improvement with respect to existing approaches.
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