EmuFog：大规模雾计算结构的可扩展和可缩放仿真
EmuFog: Extensible and Scalable Emulation of Large-Scale Fog Computing Infrastructures
摘要：
雾计算部署模型的多样性和缺乏公共可用的雾基础设施使得设计高效的应用程序或资源管理策略成为一项具有挑战性的任务。这种研究通常需要一个测试框架，以可重复和可控的方式促进对应用程序或协议设计的实验评估。在本文中，我们提出了EmuFog-一个为雾计算场景量身定制的可扩展仿真框架-它可以从头开始设计雾计算基础设施，并模拟真实的应用程序和工作负载。EmuFog使研究人员能够根据用例设计网络拓扑，在拓扑中嵌入雾计算节点，并在通过仿真网络连接的节点上运行基于Docker的应用程序。EmuFog的每个子模块都很容易扩展，尽管EmuFog为每个子模块提供了默认实现。EmuFog的可扩展性和有效性在合成和真实世界的网络拓扑结构上进行了评估。
英文摘要：
The diversity of Fog Computing deployment models and the lack of publicly available Fog infrastructure makes the design of an efficient application or resource management policy a challenging task. Such research often requires a test framework that facilitates the experimental evaluation of an application or protocol design in a repeatable and controllable manner. In this paper, we present EmuFog---an extensible emulation framework tailored for Fog Computing scenarios---that enables the from-scratch design of Fog Computing infrastructures and the emulation of real applications and workloads. EmuFog enables researchers to design the network topology according to the use-case, embed Fog Computing nodes in the topology and run Docker-based applications on those nodes connected by an emulated network. Each of the sub-modules of EmuFog are easily extensible, although EmuFog provides a default implementation for each of them. The scalability and efficacy of EmuFog are evaluated both on synthetic and real-world network topologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
