雾计算中作业调度研究综述

R. Elavarasi, S. Silas
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引用次数: 6

摘要

物联网(IoT)的发展催生了大量智能设备。物联网设备的大量增加也导致大量数据传输到云端,这反过来又增加了位置感知,缺乏移动性支持和延迟。延迟在使用云计算的关键应用程序中起着重要作用,它会导致性能的显著下降。为了克服数据量增加带来的问题,引入了雾计算。雾计算也被称为边缘计算,它可以解决某些挑战,如安全性、可靠性、资源管理、编程模型和作业调度。这篇调查报告从雾计算的定义开始,然后是雾应用,流行的问题以及雾计算的研究,并阐明了这些在雾计算未来的有用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survey on Job Scheduling in Fog Computing
The evolution of the Internet of things(IoT) has led to a massive number of intelligent devices. The tremendous increase in the IoT devices has also led to a huge amount of data transfer to the cloud that in turn increased location awareness, lack of mobility support and latency. Latency plays an important part in critical applications using cloud computing that led to a significant amount of degradation in performance. To overcome the issues due to the increase in data, fog computing was introduced. Fog computing is also called edge computing, which can address certain challenges like security, reliability, resource management, programming models, and job scheduling. This survey paper starts with the definition of fog computing followed by fog applications, prevailing issues as well as research on fog computing and also shed some light on how useful are these in the future of fog computing.
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