Please use this identifier to cite or link to this item: http://hdl.handle.net/10662/21074
Title: Continuous QoS-aware adaptation of Cloud-IoT application placements
Authors: Herrera González, Juan Luis
Berrocal Olmeda, José Javier
Forti, Stefano
Brogi, Antonio
Murillo Rodríguez, Juan Manuel
Keywords: Adaptation;Cloud computing;Fog computing;Edge computing;Microservices architecture;Internet of Things;DevOps;Adaptación;Computación en nube;Niebla informática;Computación periférica;Arquitectura de microservicios;Internet de los objetos;Internet de las cosas
Issue Date: 2023
Publisher: Springer
Abstract: Cloud-Internet of Things computing paradigms call for novel and efficient method ologies to decide where to place application services in continuity with Continuous Integration/Continuous Deployment pipelines and infrastructure monitoring. In this article, we present Continuous Adaptation (CA), a new DevOps practice for (1) detect ing runtime changes in the application requirements or the nfrastructure that, due to their change in resource consumption or their effects on the Quality of Service (QoS), can affect the validity and dependability of the current application placement, and for (2) locally intervening on them by suggesting new placements that ensure all (func tional and non-functional) application requirements are met. We assess a prototype of CA, ConDADO, and analyze its performance over a motivating use case. Con DADO adapts the application placement to environmental changes through the use of continuous reasoning, reducing the size of the problem to be solved to optimize its performance. The evaluation shows that ConDADO is able to obtain nearly optimal QoS up to 4.2× faster than alternative techniques, also minimizing the cost of service migration.
Description: Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature
URI: http://hdl.handle.net/10662/21074
ISSN: 0010-485X
DOI: 10.1007/s00607-023-01153-1
Appears in Collections:DISIT - Artículos

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