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Predictable Efficiency for Reconfiguration of Service-Oriented Systems with Concerto

Maverick Chardet 1, 2, 3 Hélène Coullon 1, 2 Christian Pérez 3
2 STACK - Software Stack for Massively Geo-Distributed Infrastructures
Inria Rennes – Bretagne Atlantique , LS2N - Laboratoire des Sciences du Numérique de Nantes
3 AVALON - Algorithms and Software Architectures for Distributed and HPC Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
Abstract : Dynamic reconfiguration of distributed software systems is nowadays gaining interest because of the emergence of dynamic IoT and smart applications as well as large scale dynamic infrastructures (e.g., Fog and Edge computing). When quality of service and experience is of prime importance, efficient reconfiguration is necessary, as well as performance predictability to decide when a reconfiguration should occur. This paper tackles the problem of efficient execution of a reconfiguration plan and its predictability with Concerto, a reconfiguration model supporting a high level of parallelism. Evaluation performed on synthetic cases and on two real production scenarios show that Concerto provides better performance than state-of-the-art systems with accurate time estimation.
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Submitted on : Friday, June 12, 2020 - 9:52:17 AM
Last modification on : Tuesday, October 6, 2020 - 3:15:00 PM

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Maverick Chardet, Hélène Coullon, Christian Pérez. Predictable Efficiency for Reconfiguration of Service-Oriented Systems with Concerto. CCGrid 2020 : 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, May 2020, Melbourne, Australia. ⟨10.1109/CCGrid49817.2020.00-59⟩. ⟨hal-02535077⟩

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