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Federated-ANN based Critical Path Analysis and Health Recommendations for MapReduce Workflows in Consumer Electronics Applications

Demirbaga, Umit; Aujla, Gagangeet Singh

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Authors

Umit Demirbaga



Abstract

Although much research has been done to improve the performance of big data systems, predicting the performance degradation of these systems quickly and efficiently remains a significant challenge. Unfortunately, the complexity of big data systems is so vast that predicting performance degradation ahead of time is quite tricky. Long execution time is often discussed in the context of performance degradation of big data systems. This paper proposes MrPath, a Federated AI-based critical path analysis approach for holistic performance prediction of MapReduce workflows for consumer electronics applications while enabling root-cause analysis of various types of faults. We have implemented a federated artificial neural network (FANN) to predict the critical path in a MapReduce workflow. After the critical path components (e.g., mapper1, reducer2) are predicted/detected, root cause analysis uses user-defined functions (UDF) to pinpoint the most likely reasons for the observed performance problems. Finally, health node classification is performed using an ANN-based Self-Organising Map (SOM). The results show that the AI-based critical path analysis method can significantly illuminate the reasons behind the long execution time in big data systems.

Citation

Demirbaga, U., & Aujla, G. S. (2023). Federated-ANN based Critical Path Analysis and Health Recommendations for MapReduce Workflows in Consumer Electronics Applications. IEEE Transactions on Consumer Electronics, 1-1. https://doi.org/10.1109/tce.2023.3318813

Journal Article Type Article
Acceptance Date Sep 21, 2023
Online Publication Date Sep 25, 2023
Publication Date 2023
Deposit Date Nov 2, 2023
Publicly Available Date Nov 3, 2023
Journal IEEE Transactions on Consumer Electronics
Print ISSN 0098-3063
Electronic ISSN 1558-4127
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Pages 1-1
DOI https://doi.org/10.1109/tce.2023.3318813
Keywords Electrical and Electronic Engineering; Media Technology
Public URL https://durham-repository.worktribe.com/output/1875624

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