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An Efficient Formal Modeling Framework for Hybrid Cloud-Fog Systems

机译:混合云系统的高效正式建模框架

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Advanced communication technologies (e.g., 5G) probably elicit a complete change of network and its applications. For example, a growing number of services begin shifting from central clouds to vast mobile devices, as the hybrid use of cloud and fog computing technologies can provide enhanced quality of service and efficient utilization of resources. However, to design such complex hybrid cloud-fog (HCF) systems, it remains a challenge to implement time-consuming modeling and inefficient evaluation in its early design stage based on the conventional simulation or practical experimentation. Therefore, how to reduce design cost and improve development efficiency becomes a crucial issue in the process of designing large-scale HCF systems. To address the issue, this paper proposes a novel modeling framework for large-scale HCF systems based on a high-level formal language, i.e. performance evaluation process algebra (PEPA). Toward the key components of an HCF system, the proposed framework includes three crucial model prototypes: compositional architecture model, abstract communication model and scheduling model. Moreover, the scheduling model is designed with a novel smart scheduling scheme that integrates two atomic scheduling algorithms and a decision module to make an efficient algorithm selection. The smart scheduling algorithm can well adapt the HCF systems by yielding stable and fast response to end-users, particularly under dynamical system conditions. Finally, the framework is the first research achieving the full potential of formal methods to implement industry-level modeling and evaluation.
机译:先进的通信技术(例如,5G)可能引起网络及其应用程序的完整变更。例如,越来越多的服务开始从中央云转移到庞大的移动设备,因为云和雾计算技术的混合使用可以提供增强的服务质量和资源的有效利用。然而,为了设计这种复杂的混合云(HCF)系统,基于传统模拟或实际实验,在其早期设计阶段实施耗时的建模和低效评估仍有挑战。因此,如何降低设计成本,提高开发效率成为设计大型HCF系统过程中的一个至关重要的问题。要解决此问题,本文提出了一种基于高级正式语言的大型HCF系统的新型建模框架,即绩效评估过程代数(Pepa)。朝向HCF系统的关键组件,所提出的框架包括三个关键模型原型:组成架构模型,抽象通信模型和调度模型。此外,调度模型被设计为具有新颖的智能调度方案,其集成了两个原子调度算法和决策模块来进行有效的算法选择。智能调度算法可以通过对最终用户产生稳定和快速的响应来良好适应HCF系统,特别是在动态系统条件下。最后,该框架是第一个研究实现行业级建模和评估的正式方法的全面潜力。

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