Process mining approach for Multi-Cloud SLA Reporting

Jeremy Mechouche; Mohamed Sellami; Zakaria Maamar; Roua Touihri; Walid Gaaloul

doi:10.1109/BigData59044.2023.10386171

Process mining approach for Multi-Cloud SLA Reporting

Jeremy Mechouche
, Mohamed Sellami
, Zakaria Maamar
, Roua Touihri
, Walid Gaaloul

Devoteam R&i
CNRS UMR 5157 SAMOVAR
University of Doha for Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Cloud consumers' requirements possess an inherent dynamic nature, characterized by fluctuating needs in reliability and high-availability relative to their workload. To satisfy these requirements, service reconfiguration strategies are put in place ensuring first, adaptable service provisioning and second, compliance with the agreed-upon Service Level Agreements (SLAs) between consumers and providers. However, deviations between SLAs and 'real' observed behaviours could occur even after triggering reconfiguration strategies. Additionally, as organizations increasingly embrace multi-cloud environments, careful consideration must be given to the inherent challenges that arise in this requirements satisfaction. In this paper, we represent these strategies as state machines used to report their conformance to collected logs which track what really happened at run-time. The collected logs are processed to construct state machines suitable for conformance checking. Experiments demonstrating the technical doability of using conformance checking to detect deviations between SLAs and logs, along with verifying the suitability of reconfiguration strategies, are also discussed in the paper.

Original language	English
Title of host publication	Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
Editors	Jingrui He, Themis Palpanas, Xiaohua Hu, Alfredo Cuzzocrea, Dejing Dou, Dominik Slezak, Wei Wang, Aleksandra Gruca, Jerry Chun-Wei Lin, Rakesh Agrawal
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5867-5876
Number of pages	10
ISBN (Electronic)	9798350324457
DOIs	https://doi.org/10.1109/BigData59044.2023.10386171
Publication status	Published - 1 Jan 2023
Event	2023 IEEE International Conference on Big Data, BigData 2023 - Sorrento, Italy Duration: 15 Dec 2023 → 18 Dec 2023

Publication series

Name	Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

Conference

Conference	2023 IEEE International Conference on Big Data, BigData 2023
Country/Territory	Italy
City	Sorrento
Period	15/12/23 → 18/12/23

Keywords

Conformance Checking
Log
Multi-Cloud
Process Mining
SLA

Access to Document

10.1109/BigData59044.2023.10386171

Cite this

Mechouche, J., Sellami, M., Maamar, Z., Touihri, R., & Gaaloul, W. (2023). Process mining approach for Multi-Cloud SLA Reporting. In J. He, T. Palpanas, X. Hu, A. Cuzzocrea, D. Dou, D. Slezak, W. Wang, A. Gruca, J. C.-W. Lin, & R. Agrawal (Eds.), Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023 (pp. 5867-5876). (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData59044.2023.10386171

Mechouche, Jeremy ; Sellami, Mohamed ; Maamar, Zakaria et al. / Process mining approach for Multi-Cloud SLA Reporting. Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. editor / Jingrui He ; Themis Palpanas ; Xiaohua Hu ; Alfredo Cuzzocrea ; Dejing Dou ; Dominik Slezak ; Wei Wang ; Aleksandra Gruca ; Jerry Chun-Wei Lin ; Rakesh Agrawal. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 5867-5876 (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023).

@inproceedings{8fcd561989594f4b8b71b0924d07f79f,

title = "Process mining approach for Multi-Cloud SLA Reporting",

abstract = "Cloud consumers' requirements possess an inherent dynamic nature, characterized by fluctuating needs in reliability and high-availability relative to their workload. To satisfy these requirements, service reconfiguration strategies are put in place ensuring first, adaptable service provisioning and second, compliance with the agreed-upon Service Level Agreements (SLAs) between consumers and providers. However, deviations between SLAs and 'real' observed behaviours could occur even after triggering reconfiguration strategies. Additionally, as organizations increasingly embrace multi-cloud environments, careful consideration must be given to the inherent challenges that arise in this requirements satisfaction. In this paper, we represent these strategies as state machines used to report their conformance to collected logs which track what really happened at run-time. The collected logs are processed to construct state machines suitable for conformance checking. Experiments demonstrating the technical doability of using conformance checking to detect deviations between SLAs and logs, along with verifying the suitability of reconfiguration strategies, are also discussed in the paper.",

keywords = "Conformance Checking, Log, Multi-Cloud, Process Mining, SLA",

author = "Jeremy Mechouche and Mohamed Sellami and Zakaria Maamar and Roua Touihri and Walid Gaaloul",

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doi = "10.1109/BigData59044.2023.10386171",

language = "English",

series = "Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023",

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editor = "Jingrui He and Themis Palpanas and Xiaohua Hu and Alfredo Cuzzocrea and Dejing Dou and Dominik Slezak and Wei Wang and Aleksandra Gruca and Lin, \{Jerry Chun-Wei\} and Rakesh Agrawal",

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Mechouche, J, Sellami, M, Maamar, Z, Touihri, R & Gaaloul, W 2023, Process mining approach for Multi-Cloud SLA Reporting. in J He, T Palpanas, X Hu, A Cuzzocrea, D Dou, D Slezak, W Wang, A Gruca, JC-W Lin & R Agrawal (eds), Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023, Institute of Electrical and Electronics Engineers Inc., pp. 5867-5876, 2023 IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, 15/12/23. https://doi.org/10.1109/BigData59044.2023.10386171

Process mining approach for Multi-Cloud SLA Reporting. / Mechouche, Jeremy; Sellami, Mohamed; Maamar, Zakaria et al.
Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. ed. / Jingrui He; Themis Palpanas; Xiaohua Hu; Alfredo Cuzzocrea; Dejing Dou; Dominik Slezak; Wei Wang; Aleksandra Gruca; Jerry Chun-Wei Lin; Rakesh Agrawal. Institute of Electrical and Electronics Engineers Inc., 2023. p. 5867-5876 (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Process mining approach for Multi-Cloud SLA Reporting

AU - Mechouche, Jeremy

AU - Sellami, Mohamed

AU - Maamar, Zakaria

AU - Touihri, Roua

AU - Gaaloul, Walid

PY - 2023/1/1

Y1 - 2023/1/1

N2 - Cloud consumers' requirements possess an inherent dynamic nature, characterized by fluctuating needs in reliability and high-availability relative to their workload. To satisfy these requirements, service reconfiguration strategies are put in place ensuring first, adaptable service provisioning and second, compliance with the agreed-upon Service Level Agreements (SLAs) between consumers and providers. However, deviations between SLAs and 'real' observed behaviours could occur even after triggering reconfiguration strategies. Additionally, as organizations increasingly embrace multi-cloud environments, careful consideration must be given to the inherent challenges that arise in this requirements satisfaction. In this paper, we represent these strategies as state machines used to report their conformance to collected logs which track what really happened at run-time. The collected logs are processed to construct state machines suitable for conformance checking. Experiments demonstrating the technical doability of using conformance checking to detect deviations between SLAs and logs, along with verifying the suitability of reconfiguration strategies, are also discussed in the paper.

AB - Cloud consumers' requirements possess an inherent dynamic nature, characterized by fluctuating needs in reliability and high-availability relative to their workload. To satisfy these requirements, service reconfiguration strategies are put in place ensuring first, adaptable service provisioning and second, compliance with the agreed-upon Service Level Agreements (SLAs) between consumers and providers. However, deviations between SLAs and 'real' observed behaviours could occur even after triggering reconfiguration strategies. Additionally, as organizations increasingly embrace multi-cloud environments, careful consideration must be given to the inherent challenges that arise in this requirements satisfaction. In this paper, we represent these strategies as state machines used to report their conformance to collected logs which track what really happened at run-time. The collected logs are processed to construct state machines suitable for conformance checking. Experiments demonstrating the technical doability of using conformance checking to detect deviations between SLAs and logs, along with verifying the suitability of reconfiguration strategies, are also discussed in the paper.

KW - Conformance Checking

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KW - Process Mining

KW - SLA

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DO - 10.1109/BigData59044.2023.10386171

M3 - Conference contribution

AN - SCOPUS:85184976297

T3 - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

SP - 5867

EP - 5876

BT - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

A2 - He, Jingrui

A2 - Palpanas, Themis

A2 - Hu, Xiaohua

A2 - Cuzzocrea, Alfredo

A2 - Dou, Dejing

A2 - Slezak, Dominik

A2 - Wang, Wei

A2 - Gruca, Aleksandra

A2 - Lin, Jerry Chun-Wei

A2 - Agrawal, Rakesh

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Big Data, BigData 2023

Y2 - 15 December 2023 through 18 December 2023

ER -

Mechouche J, Sellami M, Maamar Z, Touihri R, Gaaloul W. Process mining approach for Multi-Cloud SLA Reporting. In He J, Palpanas T, Hu X, Cuzzocrea A, Dou D, Slezak D, Wang W, Gruca A, Lin JCW, Agrawal R, editors, Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 5867-5876. (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023). doi: 10.1109/BigData59044.2023.10386171

Process mining approach for Multi-Cloud SLA Reporting

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Keywords

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