物联网应用中雾计算的能源感知资源管理:综述、分类和未来方向

Sayed Mohsen Hashemi, Amir Sahafi, Amir Masoud Rahmani, Mahdi Bohlouli
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引用次数: 0

摘要

物联网(IoT)应用的能源需求随着物联网设备的增加而增加。不断上升的成本和能源需求可能会导致严重的问题。雾计算(FC)最近作为位置感知任务、数据处理、快速计算和降低能耗的一种模型而出现。雾计算模型帮助云计算在网络边缘进行快速处理,在云计算中也发挥着至关重要的作用。由于雾服务器的快速计算,在雾系统的各个部分提出了不同的服务质量(QoS)方法,并在这方面考虑了几个质量因素。尽管QoS在雾计算中具有重要意义,但在这一领域还没有广泛的研究关注QoS和能量消耗方法。因此,本文对雾计算的使用和保障进行了研究。本文回顾了六种通用方法,讨论了2015年至2023年5月底之间发表的文章。本文的重点是评价雾计算及其能耗策略。本文根据所选择的方法进一步展示了优点、缺点、工具、评估类型和质量因素。在综述研究成果的基础上,提出了雾计算能耗管理中存在的一些有待进一步研究的问题和挑战。
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Energy‐aware resource management in fog computing for IoT applications: A review, taxonomy, and future directions
Abstract The energy demand for Internet of Things (IoT) applications is increasing with a rise in IoT devices. Rising costs and energy demands can cause serious problems. Fog computing (FC) has recently emerged as a model for location‐aware tasks, data processing, fast computing, and energy consumption reduction. The Fog computing model assists cloud computing in fast processing at the network's edge, which also exerts a vital role in cloud computing. Due to the fast computing in fog servers, different quality of service (QoS) approaches have been proposed in various sections of the fog system, and several quality factors have been considered in this regard. Despite the significance of QoS in Fog computing, no extensive study has focused on QoS and energy consumption methods in this area. Therefore, this article investigates previous research on the use and guarantee of Fog computing. This article reviews six general approaches that discuss the published articles between 2015 and late May 2023. The focal point of this paper is evaluating Fog computing and the energy consumption strategy. This article further shows the advantages, disadvantages, tools, types of evaluation, and quality factors according to the selected approaches. Based on the reviewed studies, some open issues and challenges in Fog computing energy consumption management are suggested for further study.
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