FLIC: A Distributed Fog Cache for City-Scale Applications

Jack West, Neil Klingensmith, G. Thiruvathukal
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引用次数: 2

Abstract

We present FLIC, a distributed software data caching framework for fogs that reduces network traffic and latency. FLIC is targeted toward city-scale deployments of cooperative IoT devices in which each node gathers and shares data with surrounding devices. As machine learning and other data processing techniques that require large volumes of training data are ported to low-cost and low-power IoT systems, we expect that data analysis will be moved away from the cloud. Separation from the cloud will reduce reliance on power-hungry centralized cloud-based infrastructure. However, city-scale deployments of cooperative IoT devices often connect to the Internet with cellular service, in which service charges are proportional to network usage. IoT system architects must be clever in order to keep costs down in these scenarios. To reduce the network bandwidth required to operate city-scale deployments of cooperative IoT systems, FLIC implements a distributed cache on the IoT nodes in the fog. FLIC allows the IoT network to share its data without repetitively interacting with a simple cloud storage service, reducing calls out to a backing store. Our results displayed a less than 2% miss rate on reads. Thus, allowing for only 5% of requests needing the backing store. We were also able to achieve more than 50% reduction in bytes transmitted per second.
fllic:城市规模应用的分布式雾缓存
我们提出了FLIC,一种分布式软件数据缓存框架,用于减少网络流量和延迟。FLIC的目标是城市规模的协作物联网设备部署,其中每个节点收集并与周围设备共享数据。随着机器学习和其他需要大量训练数据的数据处理技术被移植到低成本和低功耗的物联网系统中,我们预计数据分析将从云端转移出去。与云的分离将减少对耗电的集中式云基础设施的依赖。然而,城市规模部署的协作物联网设备通常通过蜂窝服务连接到互联网,其中服务费用与网络使用量成正比。为了在这些场景中降低成本,物联网系统架构师必须非常聪明。为了减少城市规模的协作物联网系统部署所需的网络带宽,FLIC在雾中的物联网节点上实现了分布式缓存。FLIC允许物联网网络共享其数据,而无需与简单的云存储服务重复交互,减少对后备存储的调用。我们的结果显示,读取错误率低于2%。因此,只允许5%的请求需要后备存储。我们还能够将每秒传输的字节减少50%以上。
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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