Servlerless Mobile Edge Computing

无服务器移动边缘计算

• 批准号: DGDND-2017-00095
• 负责人: deLara, Eyal
• 金额: $ 2.91万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: DND/NSERC Discovery Grant Supplement
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=617769
• 关键词: Servlerless; Mobile; Edge; Computing

Current mobile networks are not able to support next generation applications that require low latency or that produce large volumes of data that can overwhelm the network infrastructure in a carrier network. Examples include wearable applications that assist individuals cognitive impairments, as well as safety critical applications, such as face recognition applications for airport security and surveillance. These applications require more computational resources than those that are currently available on mobile or embedded devices. The use of servers on the wide-area cloud, however, is also not an option as these applications require low response times, or involve processing of large volumes of data from multiple sensors and cameras. To address these challenges the research community and the telecommunications industry are exploring ways to add computation and storage capabilities to the edge of the network. These approaches, variously referred to as cloudlets, micro data centers, or fog, augment the traditional cloud architecture with an additional layer of servers that are located closer to the end user, typically one-hop away.

当前的移动网络不能支持需要低延迟或产生大量数据的下一代应用，这些数据可能会使运营商网络中的网络基础设施不堪重负。例如，帮助个人认知障碍的可穿戴应用程序，以及安全关键应用程序，如用于机场安检和监控的人脸识别应用程序。与移动或嵌入式设备上当前可用的计算资源相比，这些应用程序需要更多的计算资源。然而，在广域云上使用服务器也不是一种选择，因为这些应用程序需要较低的响应时间，或者涉及处理来自多个传感器和摄像头的大量数据。为了应对这些挑战，研究界和电信业正在探索将计算和存储能力添加到网络边缘的方法。这些方法被不同地称为云小程序、微型数据中心或雾，它们在传统的云体系结构中增加了一层服务器，这些服务器位于更靠近最终用户的位置，通常距离最终用户只有一跳。