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Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers

机译:边缘技术的潜力,趋势和前景:雾,cloudlet,移动边缘和微型数据中心

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Advancements in smart devices, wearable gadgets, sensors, and communication paradigm have enabled the vision of smart cities, pervasive healthcare, augmented reality and interactive multimedia, Internet of Every Thing (loE), and cognitive assistance, to name a few. All of these visions have one thing in common, i.e., delay sensitivity and instant response. Various new technologies designed to work at the edge of the network, such as fog computing, cloudlets, mobile edge computing, and micro data centers have emerged in the near past. We use the name "edge computing" for this set of emerging technologies. Edge computing is a promising paradigm to offer the required computation and storage resources with minimal delays because of "being near" to the users or terminal devices. Edge computing aims to bring cloud resources and services at the edge of the network, as a middle layer between end user and cloud data centers, to offer prompt service response with minimal delay. Two major aims of edge computing can be denoted as: (a) minimize response delay by servicing the users' request at the network edge instead of servicing it at far located cloud data centers, and (b) minimize downward and upward traffic volumes in the network core. Minimization of network core traffic inherently brings energy efficiency and data cost reductions. Downward network traffic can be minimized by servicing set of users at network edge instead of service provider's data centers (e.g., multimedia and shared data) Content Delivery Networks (CDNs), and upward traffic can be minimized by processing and filtering raw data (e.g., sensors monitored data) and uploading the processed information to cloud. This survey presents a detailed overview of potentials, trends, and challenges of edge computing. The survey illustrates a list of most significant applications and potentials in the area of edge computing. State of the art literature on edge computing domain is included in the survey to guide readers towards the current trends and future opportunities in the area of edge computing. (C) 2017 Published by Elsevier B.V.
机译:智能设备,可穿戴设备,传感器和通信范例的进步使智能城市,普及医疗保健,增强现实和交互式多媒体,万物互联(loE)以及认知辅助等方面的愿景成为可能。所有这些愿景都有一个共同点,即延迟敏感性和即时响应。在不久的将来出现了各种设计用于网络边缘的新技术,例如雾计算,cloudlets,移动边缘计算和微数据中心。对于这套新兴技术,我们使用“边缘计算”这个名称。边缘计算是一种有前途的范例,因为它“靠近”用户或终端设备,因此可以以最小的延迟提供所需的计算和存储资源。边缘计算旨在将云资源和服务作为最终用户和云数据中心之间的中间层带到网络边缘,以最小的延迟提供及时的服务响应。边缘计算的两个主要目标可以表示为:(a)通过在网络边缘服务用户的请求,而不是在偏远的云数据中心服务用户的请求,来最大程度地减少响应延迟;以及(b)在网络核心。网络核心流量的最小化从本质上带来了能源效率和数据成本的降低。可以通过服务网络边缘的一组用户而不是服务提供商的数据中心(例如,多媒体和共享数据)内容分发网络(CDN)来最大程度地减少下行网络流量,并且可以通过处理和过滤原始数据(例如,传感器监控的数据),并将处理后的信息上传到云。这项调查详细介绍了边缘计算的潜力,趋势和挑战。该调查列出了边缘计算领域最重要的应用和潜力。本调查包括有关边缘计算领域的最新文献,以指导读者了解边缘计算领域的当前趋势和未来机会。 (C)2017由Elsevier B.V.发布

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