在雾计算环境中实现自我优化

D. Silva, José dos Santos Machado, A. Ribeiro, E. Moreno
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引用次数: 1

摘要

近年来,智能设备的数量呈指数级增长。然而,对延迟敏感的应用程序的计算需求已经增长,传统的云计算模型不再能够单独满足这类应用程序的所有需求。在这个方向上,一种新的计算范式被引入,它被称为雾计算。需要克服许多挑战,特别是与安全、功耗、与关键物联网应用程序通信的高延迟以及对QoS的需求等问题有关的挑战。我们已经向Fog和云计算提供了一个容器迁移机制,该机制支持实现优化策略,以实现不同的目标和解决资源分配问题。此外,我们的工作强调性能和延迟优化,通过基于MAPE-K控制回路的自主架构,并为分析和优化架构设计提供基础,以支持物联网应用。
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Towards self-optimisation in fog computing environments
In recent years, the number of smart devices has grown exponentially. However, the computational demand for latency-sensitive applications has grown and the traditional model of cloud computing is no longer able to meet alone all the needs of this type of application. In this direction, a new paradigm of computation was introduced, it is called Fog Computing. Many challenges need to be overcome, especially those regarding issues such as security, power consumption, high latency in communication with critical IoT applications, and need for QoS. We have presented a container migration mechanism to Fog and the cloud computing that supports the implementation of optimisation strategies to achieve different objectives and solutions to problems of resources allocation. In addition, our work emphasises the performance and latency optimisation, through an autonomic architecture based on the MAPE-K control loop, and provides a foundation for the analysis and optimisation architectures design to support IoT applications.
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