A gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers
| Autor: | Raffaele Montella, Hugo G. Reyes-Anastacio, J.L. Gonzalez-Compean, Jesus Carretero, Miguel Santiago-Duran, André Brinkmann, Gregorio Toscano Pulido |
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| Přispěvatelé: | Ministerio de Economía y Competitividad (España) |
| Rok vydání: | 2020 |
| Předmět: |
cloud storage
Cloud storage Computer Networks and Communications Computer science Distributed computing continuous delivery Cloud computing 02 engineering and technology Virtual containers Software In-memory storage 0202 electrical engineering electronic engineering information engineering Parallel patterns software pipelines Informática business.industry virtual containers 020206 networking & telecommunications Pipeline (software) Continuous delivery Software pipelines Pipeline transport in-memory storage Hardware and Architecture Software deployment parallel patterns Container (abstract data type) 020201 artificial intelligence & image processing business |
| Zdroj: | e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid instname |
| ISSN: | 0167-739X |
| Popis: | Software pipelines enable organizations to chain applications for adding value to contents (e.g., confidentially, reliability, and integrity) before either sharing them with partners or sending them to the cloud. However, the pipeline components add overhead when processing large volumes of data, which can become critical in real-world scenarios. This paper presents a gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers. In this model, the gears represent applications, whereas gearboxes represent software pipelines. This model was implemented as a collaborative system that automatically performs Gear up (by using parallel patterns) and/or Gear down (by using in-memory storage) until all gears produce uniform data processing velocities. This model reduces delays and bottlenecks produced by the heterogeneous performance of applications included in software pipelines. The new container tool has been designed to encapsulate both the collaborative system and the software pipelines into a virtual container and deploy it on IT infrastructures. We conducted case studies to evaluate the performance of when processing medical images and PDF repositories. The incorporation of a capsule to a cloud storage service for pre-processing medical imagery was also studied. The experimental evaluation revealed the feasibility of applying the gearbox model to the deployment of software pipelines in real-world scenarios as it can significantly improve the end-user service experience when pre-processing large-scale data in comparison with state-of-the-art solutions such as Sacbe and Parsl. This work has been partially supported by the “Spanish Ministerio de Economia y Competitividad ” under the project grant TIN2016-79637-P “Towards Unification of HPC and Big Data paradigms”. |
| Databáze: | OpenAIRE |
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