Liability and Trust Analysis Framework for Multi-Actor Dynamic Microservices

Uloženo v:
Podrobná bibliografie
Název: Liability and Trust Analysis Framework for Multi-Actor Dynamic Microservices
Autoři: Yacine Anser, Chrystel Gaber, Jean-Philippe Wary, Samia Bouzefrane, Méziane Yacoub, Onur Kalinagac, Gürkan Gür
Přispěvatelé: Bertram, Marie-Liesse
Zdroj: IEEE Transactions on Network and Service Management. 22:58-71
Informace o vydavateli: Institute of Electrical and Electronics Engineers (IEEE), 2025.
Rok vydání: 2025
Témata: Market research, Measurement, Monitoring, Machine Learning (ML), Service Level Agreement (SLA), Machine learning (ML), 005: Computerprogrammierung, Programme und Daten, Vectors, [INFO] Computer Science [cs], Trust, Microservice, Microservice architectures, Service level agreement (SLA), Microservices, Liability, Computer architecture, Service level agreements
Popis: Microservices architecture has become an increasingly common approach for building complex software systems. With the distributed nature of microservices, multiple actors can contribute to a service, hence affecting the dynamics of the environment and making the management of liabilities and trust more challenging. Service-Level Agreements (SLAs) are critical in that regard and any SLA violation or breach can result in significant financial damages. One major challenge is the lack of indicators to handle the liability and trust in such architectures. To address this issue, in this paper we propose a liability and trust analysis framework, namely the LASM Analysis Service (LAS), for multi-actor dynamic microservices that employs Machine Learning (ML) techniques.
Druh dokumentu: Article
Popis souboru: application/pdf
ISSN: 2373-7379
DOI: 10.1109/tnsm.2024.3417934
DOI: 10.21256/zhaw-32449
Přístupová URL adresa: https://cnam.hal.science/hal-04642127v1
https://cnam.hal.science/hal-04642127v1/document
https://doi.org/10.1109/tnsm.2024.3417934
Rights: CC BY
Přístupové číslo: edsair.doi.dedup.....f13a95b1ca4cc2cbe8017a670574a0cc
Databáze: OpenAIRE
Popis
Abstrakt:Microservices architecture has become an increasingly common approach for building complex software systems. With the distributed nature of microservices, multiple actors can contribute to a service, hence affecting the dynamics of the environment and making the management of liabilities and trust more challenging. Service-Level Agreements (SLAs) are critical in that regard and any SLA violation or breach can result in significant financial damages. One major challenge is the lack of indicators to handle the liability and trust in such architectures. To address this issue, in this paper we propose a liability and trust analysis framework, namely the LASM Analysis Service (LAS), for multi-actor dynamic microservices that employs Machine Learning (ML) techniques.
ISSN:23737379
DOI:10.1109/tnsm.2024.3417934