SODALITE@RT: Orchestrating Applications on Cloud-Edge Infrastructures

被引：18

作者：

Kumara, Indika ^{[1
]}

Mundt, Paul ^{[2
]}

Tokmakov, Kamil ^{[3
]}

Radolovic, Dragan ^{[4
]}

Maslennikov, Alexander ^{[4
]}

Sosa Gonzalez, Roman ^{[5
]}

Fernandez Fabeiro, Jorge ^{[5
]}

Quattrocchi, Giovanni ^{[6
]}

Meth, Kalman ^{[7
]}

Di Nitto, Elisabetta ^{[6
]}

Tamburri, Damian A. ^{[1
]}

Van den Heuvel, Willem-Jan ^{[1
]}

Meditskos, Georgios ^{[8
]}

机构：

[1] Eindhoven Univ Technol, Jheronimus Acad Data Sci, Sint Janssingel 92, NL-5211 DA Shertogenbosch, Netherlands

[2] Adaptant Solut AG, Munich, Germany

[3] Univ Stuttgart, Stuttgart, Germany

[4] XLAB Research, Ljubljana, Slovenia

[5] ATOS, Madrid, Spain

[6] Politecn Milan, Milan, Italy

[7] Haifa Res Lab, Haifa, Israel

[8] Ctr Res & Technol Hellas, Informat Technol Inst, Hellas, Greece

来源：

JOURNAL OF GRID COMPUTING | 2021年 / 19卷 / 03期

基金：

欧盟地平线“2020”;

关键词：

Orchestration; Cloud; Edge; Heterogeneous infrastructures; TOSCA; Containers; DEPLOYMENT;

D O I：

10.1007/s10723-021-09572-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

IoT-based applications need to be dynamically orchestrated on cloud-edge infrastructures for reasons such as performance, regulations, or cost. In this context, a crucial problem is facilitating the work of DevOps teams in deploying, monitoring, and managing such applications by providing necessary tools and platforms. The SODALITE@RT open-source framework aims at addressing this scenario. In this paper, we present the main features of the SODALITE@RT: modeling of cloud-edge resources and applications using open standards and infrastructural code, and automated deployment, monitoring, and management of the applications in the target infrastructures based on such models. The capabilities of the SODALITE@RT are demonstrated through a relevant case study.

引用

页数：23

共 44 条

[1] Fine-Grained Dynamic Resource Allocation for Big-Data Applications [J].

Baresi, Luciano ;

Leva, Alberto ;

Quattrocchi, Giovanni .

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2021, 47 (08) :1668-1682

[2]

Bellendorf J., 2019, COMPUTING, P1

[3] A Systematic Review of Cloud Modeling Languages [J].

Bergmayr, Alexander ;

Breitenbuecher, Uwe ;

Ferry, Nicolas ;

Rossini, Alessandro ;

Solberg, Arnor ;

Wimmer, Manuel ;

Kappel, Gerti ;

Leymann, Frank .

ACM COMPUTING SURVEYS, 2018, 51 (01)

[4] Portable Cloud Services Using TOSCA [J].

Binz, Tobias ;

Breiter, Gerd ;

Leymann, Frank ;

Spatzier, Thomas .

IEEE INTERNET COMPUTING, 2012, 16 (03) :80-84

[5] MODELS@ RUN.TIME [J].

Blair, Gordon ;

Bencomo, Nelly ;

France, Robert B. .

COMPUTER, 2009, 42 (10) :22-27

[6]

Borovits Nemania, 2020, MaLTeSQuE 2020: Proceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation, P7, DOI 10.1145/3416505.3423564

[7]

Brogi A., 2014, ACM SIGSOFT Software Engineering Notes, V39, P1, DOI DOI 10.1145/2557833.2557844

[8] TosKer: A synergy between TOSCA and Docker for orchestrating multicomponent applications [J].

Brogi, Antonio ;

Rinaldi, Luca ;

Soldani, Jacopo .

SOFTWARE-PRACTICE & EXPERIENCE, 2018, 48 (11) :2061-2079

[9] Towards Osmotic Computing: a Blue-Green Strategy for the Fast Re-Deployment of Microservices [J].

Buzachis, Alina ;

Galletta, Antonino ;

Celesti, Antonio ;

Carnevale, Lorenzo ;

Villari, Massimo .

2019 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2019, :70-75

[10] Deployment of Elastic Virtual Hybrid Clusters Across Cloud Sites [J].

Caballer, Miguel ;

Antonacci, Marica ;

Sustr, Zdenek ;

Perniola, Michele ;

Molto, German .

JOURNAL OF GRID COMPUTING, 2021, 19 (01)

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