A Scalable Telemetry Framework for Zero Touch Optical Network Management

L. Valcarenghi, A. Pacini, A. Sgambelluri, F. Paolucci
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引用次数: 3

Abstract

The interest about Zero Touch Network and Service Management (ZSM) is rapidly emerging. As defined by ETSI, the ZSM architecture is based on a closed-loop/feedback control of the network and the services. Such closed-loop control can be based on the Boyd’s Observe Orient Decide and Act (OODA) loop that matches some specific management functions such as Data Collection, Data Analytics, Intelligence, Orchestration and Control. An efficient implementation of such control loop allows the network to timely adapt to changes and maintain the required quality of service.Many solutions for collecting network parameters (i.e., implementing ZSM data collection) are proposed that fall under the broad umbrella of network telemetry. An example is the Google gRPC, that represented one of the first solutions to provide a framework for data collection. Since then, the number of available frameworks is proliferating. In this paper we propose the utilisation of Apache Kafka as a framework for collecting optical network parameters. Then, the paper goes beyond that by proposing and showing how Apache Kafka can be effective for supporting data exchange and management of whole ZSM closed-loop.Experimental evaluation results show that, even when a large number of data are collected, the solution is scalable and the time to disseminate the parameter values is short. Indeed, the difference between the reception time and the generation time of data is, on average, 40-50ms when about four thousand messages are generated.
零接触光网络管理的可扩展遥测框架
对零接触网络和服务管理(ZSM)的兴趣正在迅速兴起。根据ETSI的定义,ZSM体系结构基于对网络和服务的闭环/反馈控制。这种闭环控制可以基于Boyd的观察、东方、决定和行动(OODA)循环,该循环匹配一些特定的管理功能,如数据收集、数据分析、智能、编排和控制。这种控制回路的有效实施使网络能够及时适应变化并保持所需的服务质量。收集网络参数(即实现ZSM数据收集)的许多解决方案都属于网络遥测的广泛范畴。Google gRPC就是一个例子,它是最早提供数据收集框架的解决方案之一。从那时起,可用框架的数量激增。在本文中,我们提出利用Apache Kafka作为收集光网络参数的框架。然后,本文进一步提出并展示了Apache Kafka如何有效地支持整个ZSM闭环的数据交换和管理。实验评估结果表明,即使在采集大量数据的情况下,该方案也具有可扩展性和传播参数值的时间短。实际上,当生成大约4000条消息时,数据的接收时间和生成时间之间的差异平均为40-50ms。
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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