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Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applications

Östberg, Per-Olov and Le Duc, Thang and Casari, Paolo and García Leiva, Rafael and Fernández Anta, Antonio (2020) Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applications. In: Managing Distributed Cloud Applications and Infrastructure. Palgrave Studies in Digital Business & Enabling Technologies (PSDBET) . Palgrave Macmillan, pp. 51-68. ISBN 978-3-030-39862-0

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Abstract

Optimisation of (the configuration and deployment of) distributed cloud applications is a complex problem that requires understanding factors such as infrastructure and application topologies, workload arrival and propagation patterns, and the predictability and variations of user behaviour. This chapter outlines the RECAP approach to application optimisation and presents its framework for joint modelling of applications, workloads, and the propagation of workloads in applications and networks. The interaction of the models and algorithms developed is described and presented along with the tools that build on them. Contributions in modelling, characterisation, and autoscaling of applications, as well as prediction and generation of workloads, are presented and discussed in the context of optimisation of distributed cloud applications operating in complex heterogeneous resource environments.

Item Type: Book Chapters
Uncontrolled Keywords: Resource provisioning, Workload modelling, Workload prediction, Workload propagation modelling, Application optimisation, Autoscaling, Distributed cloud.
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Rebeca De Miguel
Date Deposited: 10 Nov 2020 14:23
Last Modified: 10 Nov 2020 14:23
URI: http://eprints.networks.imdea.org/id/eprint/2220

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