雾计算基础设施模拟工具集综述,用于能源估计、规划和可扩展性

Kelvin N. Lawal, T. Olaniyi, Ryan M. Gibson
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引用次数: 1

摘要

智能物联网(IoT)设备的指数级增长导致了物联网基础设施内数据生成、传输、存储和管理的增加。因此,延迟、网络带宽使用和管理数据的能耗都会增加。本文通过引入雾计算范式来扩展传统云计算连续体,从而评估能源效率的改进。使用概念验证(PoC),本研究解决了传统云计算的一些挑战,例如网络模拟工具集的高能耗。我们进行了一项评估,以确定最适合的网络模拟软件工具,用于在数据管理、规划和能源效率方面批判性地分析雾计算和传统云计算。本文通过iFogSim网络仿真工具集演示了与传统云计算架构相比,雾计算层技术的引入降低了能耗。此外,还探讨了雾计算和云计算数据中心在能源消耗和数据管理方面的差异。
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Fog Computing Infrastructure Simulation Toolset Review for Energy Estimation, Planning and Scalability
The exponential growth of smart Internet of Things (IoT) devices has led to an increase in data generation, transfer, storage, and management within IoT infrastructures. Consequently, there is an increase in latency, network bandwidth usage and energy consumption for managing data. This paper evaluates energy efficiency improvements through extending the traditional Cloud computing continuum with the introduction of the Fog computing paradigm. Using proof of concept (PoC), this research addresses some of the challenges with traditional cloud computing such as high energy consumption with network simulation toolsets. An evaluation was conducted to determine the best suited network simulation software tool for critically analysing Fog computing and traditional Cloud computing in terms of data management, planning and energy efficiency. This paper demonstrates a reduction in energy consumption with the introduction of Fog computing layer technologies when compared to traditional Cloud computing architecture through the iFogSim network simulation toolset. Furthermore, the differences in energy consumption and data management with Fog and Cloud computing data centres are explored.
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