动态雾环境下任务分配的目标函数描述评价与优化方法

Reinout Eyckerman, Siegfried Mercelis, J. Márquez-Barja, P. Hellinckx
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引用次数: 2

摘要

工业、医疗保健和其他各种部门正在迅速采用物联网来驱动信息和自动化系统。但是,随着设备数量的增加,通过网络发送的信息数量也会增加,从而导致网络拥塞和潜在的延迟增加。为了确保当前网络基础设施支持智能汽车等要求苛刻的应用程序,我们提供了一种将软件从云分发到边缘的通用方法,从而减少了延迟等多个目标。在本研究中,我们定义了多目标分布场景中的几个问题,并比较了几种定义和解决问题的方法。此外,我们提出了一种方法来降低问题的复杂性,提高性能,只略微降低准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Objective Function Descriptions And Optimization Methodologies For Task Allocation In A Dynamic Fog Environment
Industry, healthcare, and various other sectors are rapidly adopting the Internet of Things to drive information and automation systems. However, as the number of devices increases, the number of information sent over the network increases as well, inducing network congestion and a potential latency increase. To ensure that demanding applications, such as smart vehicles, are supported in the current network infrastructure, we provide a general methodology of distributing software from the cloud toward the edge, reducing multiple objectives such as latency. In this research we define several problems in multi-objective distribution scenarios, and compare several methodologies for defining and solving the problem. Additionally, we propose a method for decreasing the problem complexity, improving performance with only slightly reduced accuracy.
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