Renovation of EdgeCloudSim: An Efficient Discrete-Event Approach

Raphael Freymann, Junjie Shi, Jian-Jia Chen, Kuan-Hsun Chen
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引用次数: 3

Abstract

Due to the growing popularity of the Internet of Things, edge computing concept has been widely studied to relieve the load on the original cloud and networks while improving the service quality for end-users. To simulate such a complex environment involving edge and cloud computing, EdgeCloudSim has been widely adopted. However, it suffers from certain efficiency and scalability issues due to the ignorance of the deficiency in the originally adopted data structures and maintenance strategies. Specifically, it generates all events at beginning of the simulation and stores unnecessary historical information, both result in unnecessarily high complexity for search operations. In this work, by fixing the mismatches on the concept of discrete-event simulation, we propose enhancement of EdgeCloudSim which improves not only the runtime efficiency of simulation, but also the flexibility and scalability. Through extensive experiments with statistical methods, we show that the enhancement does not affect the expressiveness of simulations while obtaining 2 orders of magnitude speedup, especially when the device count is large.
EdgeCloudSim的改进:一种高效的离散事件方法
随着物联网的日益普及,边缘计算概念得到了广泛的研究,以减轻原有云和网络的负载,同时提高对最终用户的服务质量。为了模拟这种涉及边缘和云计算的复杂环境,EdgeCloudSim被广泛采用。然而,由于忽略了最初采用的数据结构和维护策略的不足,它在效率和可伸缩性方面存在一定的问题。具体来说,它在模拟开始时生成所有事件,并存储不必要的历史信息,这两者都导致搜索操作不必要的高复杂性。在这项工作中,通过修正离散事件仿真概念上的不匹配,我们提出了对EdgeCloudSim的增强,不仅提高了仿真的运行效率,而且提高了灵活性和可扩展性。通过统计方法的大量实验,我们表明,在获得2个数量级的加速时,这种增强不影响模拟的表达性,特别是在设备数量很大的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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