publication . Doctoral thesis . 2020

Supporter la gestion et l'orchestration des ressources cloud dans un environnement multi-nuages

Brabra, Hayet;
Open Access English
  • Published: 13 Feb 2020
  • Publisher: HAL CCSD
Abstract
With the increased adoption of cloud computing, multiple and heterogeneous configuration and management APIs/tools and platforms have been proposed to enable end-to-end management and orchestration tasks. However, this proliferation is one of the fundamental reasons that has intensified the heterogeneity issue in multiple respects, making the cloud interoperability very difficult to achieve. With the lack of interoperability, orchestrating and managing elastic cloud resources distributed across heterogeneous providers become very complex and costly missions for the cloud adopters.Towards fostering cloud interoperability, standardization is a definitive method ac...
Subjects
free text keywords: Elasticity, Multi-Cloud, Orchestration, Management, APIs, DevOps, Élasticité, Multi-nuages, Gestion, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]
65 references, page 1 of 5

1 General Introduction 15 1.1 Research context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.2 Motivation and problem statement . . . . . . . . . . . . . . . . . . . . 17 1.2.1 Interoperable management of cloud resources . . . . . . . . . . 17 1.2.2 Interoperable orchestration of cloud resources . . . . . . . . . . 20 1.2.3 Multi-cloud Elasticity of cloud resources . . . . . . . . . . . . . 22 1.3 Objectives and contributions . . . . . . . . . . . . . . . . . . . . . . . 23 1.4 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.5 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2 Background 29 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Elasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.2 Orchestration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 2.2.3 Cloud Standards . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2.3.1 OCCI . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2.3.2 TOSCA . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3 Adopted solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.3.1 Semantic Web technologies . . . . . . . . . . . . . . . . . . . . 40 2.3.2 Model-driven Engineering . . . . . . . . . . . . . . . . . . . . . 43 2.3.2.1 Model Transformations . . . . . . . . . . . . . . . . . 45 2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3 State of The Art 49 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.2 On using (anti) patterns for software design assistance . . . . . . . . . 50 3.2.1 (Anti) patterns identification . . . . . . . . . . . . . . . . . . . 50 3.2.2 (Anti) patterns modeling and formalization . . . . . . . . . . . 52 3.2.3 (Anti) patterns analysis and detection . . . . . . . . . . . . . . 53 3.2.4 Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.3 On facilitating Cloud resources orchestration . . . . . . . . . . . . . . 59 3.3.1 DevOps approaches . . . . . . . . . . . . . . . . . . . . . . . . 59 3.3.2 Standard-based approaches . . . . . . . . . . . . . . . . . . . . 62 3.3.3 Non-Standard approaches . . . . . . . . . . . . . . . . . . . . . 64 3.3.4 Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.4 On supporting Cloud resources elasticity . . . . . . . . . . . . . . . . . 69 3.4.1 Commercial and open-source solutions . . . . . . . . . . . . . . 69 3.4.2 Research solutions . . . . . . . . . . . . . . . . . . . . . . . . . 71

4 Assisting interoperable management APIs Design using patterns and anti-patterns 77 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 Identifying REST/ OCCI (Anti)patterns . . . . . . . . . . . . . . . . 79 4.2.1 REST (Anti)patterns . . . . . . . . . . . . . . . . . . . . . . . 79 4.2.2 OCCI (Anti)patterns . . . . . . . . . . . . . . . . . . . . . . . . 82 4.3 Approach Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.3.1 Definition of OCCI/REST (Anti)Patterns . . . . . . . . . . . . 87 4.3.2 Analysis and Definition of Detection rules . . . . . . . . . . . . 89 4.3.3 Detection of OCCI/REST (Anti)Patterns . . . . . . . . . . . . 92 4.4 Experiments and Validation . . . . . . . . . . . . . . . . . . . . . . . . 95 4.4.1 Proof of Concept: ORAP-Detector . . . . . . . . . . . . . . . . 95 4.4.2 Hypotheses and Experimental Setup . . . . . . . . . . . . . . . 95 4.4.3 Results Analysis and Findings . . . . . . . . . . . . . . . . . . 97 4.4.3.1 Detection of REST of (anti) patterns . . . . . . . . . 97 4.4.3.2 Detection of OCCI (anti) patterns . . . . . . . . . . . 99 4.4.3.3 Compliance Evaluation . . . . . . . . . . . . . . . . . 99 4.4.3.4 Discussion of validation results . . . . . . . . . . . . . 101 4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

[8] A., R.G., E., B., U., D.: Soa patterns. Manning Publications (2012)

[9] Akdur, D., Garousi, V., Demir¨ors, O.: A survey on modeling and model-driven engineering practices in the embedded software industry. Journal of Systems Architecture 91, 62 - 82 (2018) [OpenAIRE]

[10] Al-Dhuraibi, Y.: Flexible Framework for Elasticity in Cloud Computing. Theses, Universit´e lille1 (Dec 2018), https://tel.archives-ouvertes.fr/ tel-02011337 [OpenAIRE]

[11] Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., Merle, P.: Elasticity in cloud computing: State of the art and research challenges. IEEE Trans. Services Computing 11(2), 430-447 (2018) [OpenAIRE]

[12] Alexander, K., Lee, C., Kim, E., Helal, S.: Enabling end-to-end orchestration of multi-cloud applications. IEEE Access 5, 18862-18875 (2017)

[13] Alnusair, A., Zhao, T.: Towards a model-driven approach for reverse engineering design patterns. In: In Proc. 2nd International Workshop on Transforming and Weaving Ontologies in Model Driven Engineering (TWOMDE'09 (2009)

[14] Amazon: Amazon Web Services, available at https://aws.amazon.com/fr/

[15] Ansible: Ansible-in-depth. online article (jun 2018), available at https://www. ansible.com/resources/whitepapers/ansible-in-depth

[16] Apache-Foundation: Apache jclouds: An open source multi-cloud toolki, https://jclouds.apache.org/

[31] Bhattacharjee, A., Barve, Y., Gokhale, A., Kuroda, T.: A model-driven approach to automate the deployment and management of cloud services. In: 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion). pp. 109-114 (Dec 2018)

[32] Brabra, H., Mtibaa, A., Gaaloul, W., Benatallah, B., Gargouri, F.: Modeldriven orchestration for cloud resources. In: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). pp. 422-429 (July 2019) [OpenAIRE]

65 references, page 1 of 5
Abstract
With the increased adoption of cloud computing, multiple and heterogeneous configuration and management APIs/tools and platforms have been proposed to enable end-to-end management and orchestration tasks. However, this proliferation is one of the fundamental reasons that has intensified the heterogeneity issue in multiple respects, making the cloud interoperability very difficult to achieve. With the lack of interoperability, orchestrating and managing elastic cloud resources distributed across heterogeneous providers become very complex and costly missions for the cloud adopters.Towards fostering cloud interoperability, standardization is a definitive method ac...
Subjects
free text keywords: Elasticity, Multi-Cloud, Orchestration, Management, APIs, DevOps, Élasticité, Multi-nuages, Gestion, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]
65 references, page 1 of 5

1 General Introduction 15 1.1 Research context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.2 Motivation and problem statement . . . . . . . . . . . . . . . . . . . . 17 1.2.1 Interoperable management of cloud resources . . . . . . . . . . 17 1.2.2 Interoperable orchestration of cloud resources . . . . . . . . . . 20 1.2.3 Multi-cloud Elasticity of cloud resources . . . . . . . . . . . . . 22 1.3 Objectives and contributions . . . . . . . . . . . . . . . . . . . . . . . 23 1.4 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.5 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2 Background 29 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Elasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.2 Orchestration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 2.2.3 Cloud Standards . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2.3.1 OCCI . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2.3.2 TOSCA . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3 Adopted solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.3.1 Semantic Web technologies . . . . . . . . . . . . . . . . . . . . 40 2.3.2 Model-driven Engineering . . . . . . . . . . . . . . . . . . . . . 43 2.3.2.1 Model Transformations . . . . . . . . . . . . . . . . . 45 2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3 State of The Art 49 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.2 On using (anti) patterns for software design assistance . . . . . . . . . 50 3.2.1 (Anti) patterns identification . . . . . . . . . . . . . . . . . . . 50 3.2.2 (Anti) patterns modeling and formalization . . . . . . . . . . . 52 3.2.3 (Anti) patterns analysis and detection . . . . . . . . . . . . . . 53 3.2.4 Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.3 On facilitating Cloud resources orchestration . . . . . . . . . . . . . . 59 3.3.1 DevOps approaches . . . . . . . . . . . . . . . . . . . . . . . . 59 3.3.2 Standard-based approaches . . . . . . . . . . . . . . . . . . . . 62 3.3.3 Non-Standard approaches . . . . . . . . . . . . . . . . . . . . . 64 3.3.4 Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.4 On supporting Cloud resources elasticity . . . . . . . . . . . . . . . . . 69 3.4.1 Commercial and open-source solutions . . . . . . . . . . . . . . 69 3.4.2 Research solutions . . . . . . . . . . . . . . . . . . . . . . . . . 71

4 Assisting interoperable management APIs Design using patterns and anti-patterns 77 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 Identifying REST/ OCCI (Anti)patterns . . . . . . . . . . . . . . . . 79 4.2.1 REST (Anti)patterns . . . . . . . . . . . . . . . . . . . . . . . 79 4.2.2 OCCI (Anti)patterns . . . . . . . . . . . . . . . . . . . . . . . . 82 4.3 Approach Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.3.1 Definition of OCCI/REST (Anti)Patterns . . . . . . . . . . . . 87 4.3.2 Analysis and Definition of Detection rules . . . . . . . . . . . . 89 4.3.3 Detection of OCCI/REST (Anti)Patterns . . . . . . . . . . . . 92 4.4 Experiments and Validation . . . . . . . . . . . . . . . . . . . . . . . . 95 4.4.1 Proof of Concept: ORAP-Detector . . . . . . . . . . . . . . . . 95 4.4.2 Hypotheses and Experimental Setup . . . . . . . . . . . . . . . 95 4.4.3 Results Analysis and Findings . . . . . . . . . . . . . . . . . . 97 4.4.3.1 Detection of REST of (anti) patterns . . . . . . . . . 97 4.4.3.2 Detection of OCCI (anti) patterns . . . . . . . . . . . 99 4.4.3.3 Compliance Evaluation . . . . . . . . . . . . . . . . . 99 4.4.3.4 Discussion of validation results . . . . . . . . . . . . . 101 4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

[8] A., R.G., E., B., U., D.: Soa patterns. Manning Publications (2012)

[9] Akdur, D., Garousi, V., Demir¨ors, O.: A survey on modeling and model-driven engineering practices in the embedded software industry. Journal of Systems Architecture 91, 62 - 82 (2018) [OpenAIRE]

[10] Al-Dhuraibi, Y.: Flexible Framework for Elasticity in Cloud Computing. Theses, Universit´e lille1 (Dec 2018), https://tel.archives-ouvertes.fr/ tel-02011337 [OpenAIRE]

[11] Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., Merle, P.: Elasticity in cloud computing: State of the art and research challenges. IEEE Trans. Services Computing 11(2), 430-447 (2018) [OpenAIRE]

[12] Alexander, K., Lee, C., Kim, E., Helal, S.: Enabling end-to-end orchestration of multi-cloud applications. IEEE Access 5, 18862-18875 (2017)

[13] Alnusair, A., Zhao, T.: Towards a model-driven approach for reverse engineering design patterns. In: In Proc. 2nd International Workshop on Transforming and Weaving Ontologies in Model Driven Engineering (TWOMDE'09 (2009)

[14] Amazon: Amazon Web Services, available at https://aws.amazon.com/fr/

[15] Ansible: Ansible-in-depth. online article (jun 2018), available at https://www. ansible.com/resources/whitepapers/ansible-in-depth

[16] Apache-Foundation: Apache jclouds: An open source multi-cloud toolki, https://jclouds.apache.org/

[31] Bhattacharjee, A., Barve, Y., Gokhale, A., Kuroda, T.: A model-driven approach to automate the deployment and management of cloud services. In: 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion). pp. 109-114 (Dec 2018)

[32] Brabra, H., Mtibaa, A., Gaaloul, W., Benatallah, B., Gargouri, F.: Modeldriven orchestration for cloud resources. In: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). pp. 422-429 (July 2019) [OpenAIRE]

65 references, page 1 of 5
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