4.6 Article

Multi-Level Resource Sharing Framework Using Collaborative Fog Environment for Smart Cities

期刊

IEEE ACCESS
卷 9, 期 -, 页码 21859-21869

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3054420

关键词

Task analysis; Performance evaluation; Quality of service; Resource management; Edge computing; Computational modeling; Logic gates; Fog computing; IoT; resource management; fog simulators; OMNeT plus plus

资金

  1. United Arab Emirates (UAE) University UAEU Program for Advanced Research (UPAR) Research Grant Program [31T122]

向作者/读者索取更多资源

This paper proposes a simulation framework for fog devices that can use end devices to handle peak computation load for better Quality of Services. Regional fog nodes deployed at network edge locations are used as intelligent agents. The concept of using IoT devices as fog nodes has improved system performance.
Fog computing has proved its importance over legacy cloud architectures for computation, storage, and communication where edge devices are used to facilitate the delay-sensitive applications. The inception of fog nodes has brought computing intelligence close to the end-devices. Many fog computing frameworks have been proposed where edge devices are used for computation. In this paper, we proposed a simulation framework for fog devices that can use end devices to handle the peak computation load to provide better Quality of Services (QoS). The regional fog nodes are deployed at network edge locations which are used as an intelligent agent to handle the computation requests by either scheduling them on local servers, cloud data centers, or at the under-utilized end-user devices. The proposed device-to-device resource sharing model relies on Ant Colony Optimization (ACO) and Earliest Deadline First(EDF) Algorithm to provide a better quality of service using device available at multi-layer design. The concept of using IoT devices as fog nodes has improved the performance of legacy fog based systems. The proposed work is benchmarked in terms of system cost, efficiency, energy, and quality of service. Further, the proposed framework is with xFogSim in terms of task efficiency.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据