Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing

Koustabh Dolui, S. K. Datta
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引用次数: 380

Abstract

When it comes to storage and computation of large scales of data, Cloud Computing has acted as the de-facto solution over the past decade. However, with the massive growth in intelligent and mobile devices coupled with technologies like Internet of Things (IoT), V2X Communications, Augmented Reality (AR), the focus has shifted towards gaining real-time responses along with support for context-awareness and mobility. Due to the delays induced on the Wide Area Network (WAN) and location agnostic provisioning of resources on the cloud, there is a need to bring the features of the cloud closer to the consumer devices. This led to the birth of the Edge Computing paradigm which aims to provide context aware storage and distributed Computing at the edge of the networks. In this paper, we discuss the three different implementations of Edge Computing namely Fog Computing, Cloudlet and Mobile Edge Computing in detail and compare their features. We define a set of parameters based on which one of these implementations can be chosen optimally given a particular use-case or application and present a decision tree for the selection of the optimal implementation.
边缘计算实现的比较:雾计算、云计算和移动边缘计算
当涉及到大规模数据的存储和计算时,云计算在过去十年中已经成为事实上的解决方案。然而,随着智能和移动设备的大量增长,加上物联网(IoT)、V2X通信、增强现实(AR)等技术,重点已转向获得实时响应以及对上下文感知和移动性的支持。由于广域网(WAN)上的延迟和云上资源的位置不可知供应,有必要使云的功能更接近消费者设备。这导致了边缘计算范式的诞生,该范式旨在提供网络边缘的上下文感知存储和分布式计算。在本文中,我们详细讨论了三种不同的边缘计算实现,即雾计算、Cloudlet和移动边缘计算,并比较了它们的特点。我们定义了一组参数,在给定特定用例或应用程序的情况下,可以根据这些实现中的一个进行最佳选择,并为选择最佳实现提供决策树。
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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