A Novel Approach to Distributed Model Aggregation using Apache Kafka

S. Bano, E. Carlini, P. Cassará, M. Coppola, Patrizio Dazzi, A. Gotta
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引用次数: 1

Abstract

Multi-Access Edge Computing (MEC) is attracting a lot of interest because it complements cloud-based approaches. Indeed, MEC is opening up in the direction of reducing both interaction delays and data sharing, called Cyber-Physical Systems (CPSs). In the near fu- ture, edge technologies will be a fundamental tool to better support time-dependent and data-intensive applications. In this context, this work explores existing and emerging platforms for MEC and human-centric applications, and proposes a suitable architecture that can be used in the context of autonomous vehicle systems.The proposed architecture will support scalable communication among sensing devices and edge/cloud computing platforms, as well as orchestrate services for computing, storage, and learning with the use of an Information-centric paradigm such as Apache Kafka
一种使用Apache Kafka实现分布式模型聚合的新方法
多访问边缘计算(MEC)吸引了很多人的兴趣,因为它补充了基于云的方法。事实上,MEC正在朝着减少交互延迟和数据共享的方向发展,称为信息物理系统(cps)。在不久的将来,边缘技术将成为更好地支持时间依赖性和数据密集型应用的基本工具。在此背景下,本工作探索了MEC和以人为中心的应用的现有和新兴平台,并提出了可用于自动驾驶车辆系统的合适架构。提议的架构将支持传感设备和边缘/云计算平台之间的可扩展通信,以及使用以信息为中心的范式(如Apache Kafka)来编排计算、存储和学习服务
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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