基于多种群遗传算法的Fog-IoT计算中qos感知服务组合

Idir Aoudia, L. Kahloul, Saber Benharzallah, O. Kazar
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引用次数: 6

摘要

物联网(Internet of things, IoT)是信息空间与物理空间的融合,在很多地方越来越受欢迎。在本文中,我们将提出基于多种群遗传算法的基于雾-物联网计算的QoS服务组合方法,物联网云架构问题导致我们使用在雾计算系统上实现的5层架构,特别是传输层。我们的工作重点是这个传输层,我们将其分为四个子层(安全、存储、预处理和监控),这使我们具有很大的优势。其次,我们实现了基于QoS模型的多种群遗传算法(MPGA),我们考虑了QoS的7个维度,即成本、响应时间、可靠性、声誉、位置、安全性和可用性。实验结果表明,MPGA在适应度值和执行时间方面都取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QoS-aware service composition in Fog-IoT computing using multi-population genetic algorithm
The Internet of things (IoT) is the integration of information space and physical space, becoming more and more popular in several places. In this paper, we will present QoS service composition approach based on multi-population genetic algorithm based on Fog-IoT computing, IoT-cloud architecture problems led us to use the 5-layared architecture implemented on a Fog computing system especially the transport layer. Our work was focus on this transport layer where we divided it into four sub-layers (security, storage, pre-processing & monitoring), it allows us to have promising advantages. Secondly, we implemented a multi-population genetic algorithm (MPGA) based on a QoS model, we considered seven QoS dimensions, i.e. Cost, response time, reliability, reputation, location, security and availability. Experimental results show the excellent results of MPGA in terms of fitness value and execution time to handle our ambulance emergency study case.
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