Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities
Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities
复制标题
智慧城市中基于物联网的能源管理的智能边缘计算
DOI：
10.1109/mnet.2019.1800254
复制
发表时间：
2019-03-01
期刊：
影响因子：
9.3
通讯作者：
Zhang, Yan
中科院分区：
文献类型：
--
作者：
Liu, Yi;Yang, Chao;Zhang, Yan
近年来，随着智能城市的爆炸式发展，绿色能源管理系统（智能电网、智能建筑等）受到了巨大的研究和工业关注。通过引入物联网（IoT）技术，智慧城市能够通过无处不在的监控和可靠的通信实现精细的能源管理。然而，在使用基于物联网的网络结构时，长期能源效率已成为一个重要问题。在这篇文章中，我们专注于设计一个基于物联网的能源管理系统，该系统基于边缘计算基础设施和深度强化学习。首先，概述了智慧城市中基于物联网的能源管理。然后提出了一个基于物联网的边缘计算系统的框架和软件模型。在此之后，我们提出了一个有效的能源调度方案与深度强化学习的建议框架。最后，我们说明了所提出的计划的有效性。
In recent years, green energy management systems (smart grid, smart buildings, and so on) have received huge research and industrial attention with the explosive development of smart cities. By introducing Internet of Things (IoT) technology, smart cities are able to achieve exquisite energy management by ubiquitous monitoring and reliable communications. However, long-term energy efficiency has become an important issue when using an IoT-based network structure. In this article, we focus on designing an IoT-based energy management system based on edge computing infrastructure with deep reinforcement learning. First, an overview of IoT-based energy management in smart cities is described. Then the framework and software model of an IoT-based system with edge computing are proposed. After that, we present an efficient energy scheduling scheme with deep reinforcement learning for the proposed framework. Finally, we illustrate the effectiveness of the proposed scheme.