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Detection of SLA violation for big data analytics applications in cloud

journal contribution
posted on 2023-05-20, 20:55 authored by Zeng, X, Saurabh GargSaurabh Garg, Barika, M, Bista, S, Puthal, D, Zomaya, A, Ranjan, R
SLA violations do happen in real world. An SLA violation represents the failure of guaranteeing a service, which leads to unwanted consequences such as penalty payments, profit margin reduction, reputation degradation, customer churn and service interruptions. Hence, in the context of cloud-hosted big data analytics applications (BDAAs), it is paramount for providers to predict and prevent SLA violations. While machine learning-based techniques have been applied to detect SLA violations for web service or general cloud service, the study on detecting SLA violations dedicated for cloud-hosted BDAAs is still lacking. In this paper, we propose four machine learning techniques and integrate 12 resampling methods to detect SLA violations for batch-based BDAAs in the cloud. We evaluate the efficiency of the proposed techniques in comparison with ideal and baseline classifiers based on a real-world trace dataset (Alibaba). Our work not only helps providers to choose the best performing prediction technique, but also provides them capabilities to uncover the hidden pattern of multiple configurations of BDAAs across layers.


Publication title

IEEE Transactions on Computers






School of Information and Communication Technology


Institute of Electrical and Electronics Engineers

Place of publication

United States

Rights statement

Copyright 2020 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Computer systems