Demo: AIML-as-a-Service for SLA management of a Digital Twin Virtual Network Service

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2021-05-10 DOI:10.1109/INFOCOMWKSHPS51825.2021.9484610

J. Baranda, J. Mangues‐Bafalluy, E. Zeydan, C. Casetti, C. Chiasserini, M. Malinverno, C. Puligheddu, M. Groshev, C. Guimarães, Konstantin Tomakh, D. Kucherenko, O. Kolodiazhnyi

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引用次数: 6

Abstract

This demonstration presents an AI/ML platform that is offered as a service (AIMLaaS) and integrated in the management and orchestration (MANO) workflow defined in the project 5Growth following the recommendations of various standardization organizations. In such a system, SLA management decisions (scaling, in this demo) are taken at runtime by AI/ML models that are requested and downloaded by the MANO stack from the AI/ML platform at instantiation time, according to the service definition. Relevant metrics to be injected into the model are also automatically configured so that they are collected, ingested, and consumed along the deployed data engineering pipeline. The use case to which it is applied is a digital twin service, whose control and motion planning function has stringent latency constraints (directly linked to its CPU consumption), eventually determining the need for scaling out/in to fulfill the SLA.

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演示:用于数字孪生虚拟网络服务SLA管理的AIML-as-a-Service

此演示展示了一个AI/ML平台，该平台作为服务(AIMLaaS)提供，并按照各种标准化组织的建议集成到项目5Growth中定义的管理和编排(MANO)工作流中。在这样的系统中，SLA管理决策(在本演示中是扩展)是由AI/ML模型在运行时做出的，这些模型在实例化时由MANO堆栈从AI/ML平台请求和下载，根据服务定义。要注入模型的相关度量也会自动配置，以便沿着部署的数据工程管道收集、摄取和使用它们。它应用的用例是一个数字孪生服务，其控制和运动规划功能具有严格的延迟限制(直接与其CPU消耗相关)，最终决定了向外/向内扩展以实现SLA的需要。

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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IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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