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An Edge Computing Paradigm for Time-Sensitive Applications

机译：时间敏感型应用程序的边缘计算范例

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Edge computing (EC) is a new developing computing technology where data are collected, and analysed nearer to the edge or sources of the data. Cloud to the edge, intelligent applications and analytics are part of the IoT applications and technology. Edge computing technology aims to bring cloud computing features near to edge devices. For time-sensitive applications in cloud computing, architecture massive volume of data is generated at the edge and stored and analysed in the cloud. Cloud infrastructure is a composition of data centres and large-scale networks, which provides reliable services to users. Traditional cloud computing is inefficient due to delay in response, network delay and congestion as simultaneous transactions to the cloud, which is a centralised system. This paper presents a literature review on cloud-based edge computing technologies for delay-sensitive applications and suggests a conceptual model of edge computing architecture. Further, the paper also presents the implementation of QoS support edge computing paradigm in Python for further research to improve the latency and throughput for time-sensitive applications.
机译：边缘计算（EC）是一种新兴的计算技术，其中收集数据并在靠近数据边缘或数据源的位置进行分析。云到边缘，智能应用程序和分析是物联网应用程序和技术的一部分。边缘计算技术旨在将云计算功能带到边缘设备附近。对于云计算中时间紧迫的应用程序，架构会在边缘生成大量数据，并在云中进行存储和分析。云基础架构是数据中心和大规模网络的组成部分，可为用户提供可靠的服务。传统的云计算效率低下，原因是响应延迟，网络延迟和拥塞（作为对集中式系统的云的同步交易）。本文介绍了针对延迟敏感型应用的基于云的边缘计算技术的文献综述，并提出了边缘计算架构的概念模型。此外，本文还介绍了QoS支持边缘计算范例在Python中的实现，以进行进一步的研究以改善对时间敏感的应用程序的延迟和吞吐量。

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