A Quantitative Approach to Coordinated Scaling of Resources in Complex Cloud Computing Workflows-Reference-Cited by-同舟云学术

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A Quantitative Approach to Coordinated Scaling of Resources in Complex Cloud Computing Workflows

Published:2023 Issue: Volume: Page:309-324
ISSN:0302-9743
Container-title:Computer Performance Engineering and Stochastic Modelling
language:
Short-container-title:

Author:

Carnevali Laura,Paolieri Marco,Picano Benedetta,Reali Riccardo,Scommegna Leonardo,Vicario Enrico

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43185-2_21

Reference40 articles.

1. Ali-Eldin, A., Tordsson, J., Elmroth, E.: An adaptive hybrid elasticity controller for cloud infrastructures. In: IEEE Network Operations and Management Symposium, pp. 204–212. IEEE (2012)

2. Alshuqayran, N., Ali, N., Evans, R.: A systematic mapping study in microservice architecture. In: IEEE International Conference on SO Computing and Applications, pp. 44–51. IEEE (2016)

3. Bauer, A., Herbst, N., Spinner, S., Ali-Eldin, A., Kounev, S.: Chameleon: a hybrid, proactive auto-scaling mechanism on a level-playing field. IEEE Trans. Parallel Distrib. Syst. 30(4), 800–813 (2018)

4. Bauer, A., Lesch, V., Versluis, L., Ilyushkin, A., Herbst, N., Kounev, S.: Chamulteon: coordinated auto-scaling of micro-services. In: IEEE International Conference on Distributed Computing Systems, pp. 2015–2025. IEEE (2019)

5. Berg, B., Dorsman, J.L., Harchol-Balter, M.: Towards optimality in parallel scheduling. Proc. ACM Meas. Anal. Comput. Syst. 1(2), 40:1–40:30 (2017)

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1. Elastic Autoscaling for Distributed Workflows in MEC Networks;Lecture Notes on Data Engineering and Communications Technologies;2024

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