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Long-Term Preservation of Data Analysis Software with Operating-System-Level Virtualization

Eichhorn, Helge ; Trinkel, Thomas ; Anderl, Reiner (2015)
Long-Term Preservation of Data Analysis Software with Operating-System-Level Virtualization.
PV Conference. Darmstadt (03.11.2015-05.11.2015)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

A lot of today's computer-aided engineering tasks, such as data analysis, are computationally expensive, highly domain- or problem-specific, and of high complexity. Due to this fact commercial off-the-shelf software solutions do not satisfy the requirements of many organizations and custom software tools are developed. For the sake of knowledge management and traceability it should be possible to reproduce and modify such analyses with minimal effort in future engineering processes. It is not sufficient though to archive source code together with input data since every program generally relies on an extensive dependency tree. An emerging trend in the cloud computing industry is the move towards OS-level virtualization technologies, so-called containers. Within containers applications and their dependencies are packaged. We propose a workflow for archiving of custom software tools based on a hybrid virtualization strategy. A real world example is developed and implemented with the Docker container platform. Finally performance overhead and storage requirements are compared to VM-based solutions.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2015
Autor(en): Eichhorn, Helge ; Trinkel, Thomas ; Anderl, Reiner
Art des Eintrags: Bibliographie
Titel: Long-Term Preservation of Data Analysis Software with Operating-System-Level Virtualization
Sprache: Englisch
Publikationsjahr: November 2015
Veranstaltungstitel: PV Conference
Veranstaltungsort: Darmstadt
Veranstaltungsdatum: 03.11.2015-05.11.2015
Kurzbeschreibung (Abstract):

A lot of today's computer-aided engineering tasks, such as data analysis, are computationally expensive, highly domain- or problem-specific, and of high complexity. Due to this fact commercial off-the-shelf software solutions do not satisfy the requirements of many organizations and custom software tools are developed. For the sake of knowledge management and traceability it should be possible to reproduce and modify such analyses with minimal effort in future engineering processes. It is not sufficient though to archive source code together with input data since every program generally relies on an extensive dependency tree. An emerging trend in the cloud computing industry is the move towards OS-level virtualization technologies, so-called containers. Within containers applications and their dependencies are packaged. We propose a workflow for archiving of custom software tools based on a hybrid virtualization strategy. A real world example is developed and implemented with the Docker container platform. Finally performance overhead and storage requirements are compared to VM-based solutions.

Freie Schlagworte: data analysis, container-based virtualization, docker, software archiving
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau > Fachgebiet Datenverarbeitung in der Konstruktion (DiK) (ab 01.09.2022 umbenannt in "Product Life Cycle Management")
16 Fachbereich Maschinenbau
Hinterlegungsdatum: 19 Nov 2015 15:51
Letzte Änderung: 19 Nov 2015 15:51
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