PEaF-Production Environment Analyzer Framework: Assisting Continuous Deployment of 5G Workloads Using AI/ML

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Access Pub Date : 2024-10-03 DOI:10.1109/ACCESS.2024.3472498

Karthikeyan Subramaniam;Senthil Kumar;Asutosh Mishra;Ayush Bhandari;Jamsheed Manja Ppallan;Ganesh Chandrasekaran

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引用次数: 0

Abstract

A Production Environment Analyzer Framework (PEaF) is proposed to address the limitations of the Continuous Deployment (CD) process for 5G workflow lifecycle management. By integrating an AI/ML-based PEaF into the CD pipeline, we aim to ensure reliable deployments. PEaF uses AI/ML techniques to analyze the production environment and predict the health status of the hardware components. It collects raw data, applies K-Means clustering to group similar data points, and assigns scores to each cluster. These scores serve as features for training Support Vector Machine (SVM) and Random Forest (RF) classifiers to classify hardware health status. Experimental results show that PEaF achieves high classification accuracies of 97.26% and 96.44% for SVM and RF, respectively, with clustering. By analyzing the production environment and excluding deteriorating hardware from the CD, service failures are reduced by at least 27.04%. Moreover, PEaF decreases the polling frequency of hardware status by 48.7%, enhancing operational efficiency. Overall, PEaF contributes to advancing Continuous Integration/Continuous Deployment (CI/CD) practices in the 5G ecosystem, ensuring the reliability and stability of the production environment before deploying/upgrading services.

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PEaF--生产环境分析框架：利用人工智能/移动语言协助 5G 工作负载的持续部署

我们提出了一个生产环境分析框架（PEaF），以解决 5G 工作流生命周期管理中持续部署（CD）流程的局限性。通过将基于 AI/ML 的 PEaF 集成到 CD 管道中，我们旨在确保可靠的部署。PEaF 使用人工智能/ML 技术分析生产环境，预测硬件组件的健康状况。它收集原始数据，应用 K-Means 聚类将相似的数据点分组，并为每个聚类分配分数。这些分数作为训练支持向量机（SVM）和随机森林（RF）分类器的特征，用于对硬件健康状况进行分类。实验结果表明，PEaF 对 SVM 和 RF 进行聚类后，分类准确率分别达到 97.26% 和 96.44%。通过分析生产环境并从 CD 中排除恶化的硬件，服务故障至少减少了 27.04%。此外，PEaF 还将硬件状态的轮询频率降低了 48.7%，从而提高了运行效率。总体而言，PEaF 有助于推进 5G 生态系统中的持续集成/持续部署（CI/CD）实践，在部署/升级服务之前确保生产环境的可靠性和稳定性。

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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来源期刊

IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

9.80

自引率

7.70%

发文量

6673

审稿时长

6 weeks

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