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A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms: Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet

机译:终端云策划网络计算范式的调查:透明计算,移动边缘计算,雾计算和Cloudlet

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摘要

Sending data to the cloud for analysiswas a prominent trend during the past decades, driving cloud computing as a dominant computing paradigm. However, the dramatically increasing number of devices and data traffic in the Internet-of-Things (IoT) era are posing significant burdens on the capacity-limited Internet and uncontrollable service delay. It becomes difficult to meet the delay-sensitive and context-aware service requirements of IoT applications by using cloud computing alone. Facing these challenges, computing paradigms are shifting from the centralized cloud computing to distributed edge computing. Several new computing paradigms, including Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet, have emerged to leverage the distributed resources at network edge to provide timely and context-aware services. By integrating end devices, edge servers, and cloud, they form a hierarchical IoT architecture, i.e., End-Edge-Cloud orchestrated architecture to improve the performance of IoT systems. This article presents a comprehensive survey of these emerging computing paradigms from the perspective of end-edge-cloud orchestration. Specifically, we first introduce and compare the architectures and characteristics of different computing paradigms. Then, a comprehensive survey is presented to discuss state-of-the-art research in terms of computation offloading, caching, security, and privacy. Finally, some potential research directions are envisioned for fostering continuous research efforts.
机译:将数据发送到云以进行分析,在过去几十年中突出趋势,将云计算作为主导计算范例。然而,在互联网上越来越大的设备和数据流量(物联网)时代在容量有限的因特网和无法控制的服务延迟上构成了显着的负担。单独使用云计算变得难以满足IOT应用程序的延迟敏感和上下文感知服务要求。面对这些挑战,计算范例从集中云计算转换到分布式边缘计算。出现了几种新的计算范例,包括透明计算,移动边缘计算,雾计算和Cloudlet,以利用网络边缘的分布式资源来提供及时和上下文感知服务。通过集成端设备,边缘服务器和云,它们形成分层IOT架构,即终端云策划体系结构,以提高IOT系统的性能。本文从终端边缘云编队的角度介绍了对这些新兴计算范例的全面调查。具体而言,我们首先介绍并比较不同计算范例的架构和特征。然后,提出了全面的调查,以讨论计算卸载,缓存,安全和隐私的最先进的研究。最后,设想了一些潜在的研究方向,以促进持续的研究工作。

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