一种混合方法:基于模糊逻辑和遗传算法的不确定可配置QoT-IoT组合

Soura Boulaares, S. Sassi, D. Benslimane, S. Faiz
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引用次数: 0

摘要

物联网(IoT)系统与物联网(QoT)系统的结合可能具有挑战性,因为连接的设备数量巨大,应用程序和服务类型多样,网络条件各异。在构成这些事物的过程中,异质性作为一种不确定性而出现。因此,不确定性和不精确性是事物过多以及合成路径多样性的结果。解决这些挑战的一种方法是使用模糊逻辑来模拟不确定性和不精确性建模,并使用遗传算法来找到最佳路径。因此,我们提出了一个基于QoT非功能属性的Thing行为模型。此外,我们还提出了一种基于模糊逻辑和遗传算法的可配置成分不确定性建模的混合方法。我们的方法有助于确保物联网应用程序和服务获得有效运行所需的资源,即使在网络条件和需求不断变化的情况下也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid approach: Uncertain configurable QoT-IoT composition based on fuzzy logic and genetic algorithm
The combination of Quality of Thing (QoT) with Internet of Things (IoT) systems can be challenging because of the vast number of connected devices, diverse types of applications and services, and varying network conditions. During the process of composing these Things, heterogeneity arises as an uncertainty. Hence, uncertainty and imprecision emerge as a consequence of the plethora of things as well as the variety of the composition paths. One way to address these challenges is through the use of fuzzy logic to mimic uncertainty and imprecision modeling and genetic algorithm to find the optimal path. As a result, we propose a model for the Thing behaviour based on QoT non-functional properties. As well as we propose a hybrid approach for modeling the uncertainty of the configurable composition based on fuzzy logic and genetic algorithm. Our approach helps to ensure that IoT applications and services receive the resources they need to function effectively, even in the presence of varying network conditions and changing demands.
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CiteScore
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