Dynamic resource allocation is the mechanism that allows one to change the resources associated with applications at runtime and match their actual needs. The autoscaling solutions offered by cloud infrastructures are probably the most widely-used incarnation of this concepts. Originally conceived to manage virtual machines according to user-defined rules, they are now much more sophisticated and can also allocate containers (lighter than virtual machines). This paper surveys the autoscaling solutions provided by the major cloud vendors and analyzes the services they provide. It also compares them against the solution we developed, called COCOS autoscaling. We simulated the different proposals and fed them with diverse workloads. Obtained results show that COCOS autoscaling outperforms its competitors in most of the cases: it optimizes resource allocation and keeps applications' response times under set thresholds.

A Simulation-based Comparison between Industrial Autoscaling Solutions and COCOS for Cloud Applications / L. Baresi, G. Quattrocchi - In: 2020 IEEE International Conference on Web Services (ICWS)[s.l] : IEEE, 2020. - ISBN 978-1-7281-8786-0. - pp. 94-101 (( 13. ICWS Beijing 2020 [10.1109/ICWS49710.2020.00020].

A Simulation-based Comparison between Industrial Autoscaling Solutions and COCOS for Cloud Applications

G. Quattrocchi
Ultimo
2020

Abstract

Dynamic resource allocation is the mechanism that allows one to change the resources associated with applications at runtime and match their actual needs. The autoscaling solutions offered by cloud infrastructures are probably the most widely-used incarnation of this concepts. Originally conceived to manage virtual machines according to user-defined rules, they are now much more sophisticated and can also allocate containers (lighter than virtual machines). This paper surveys the autoscaling solutions provided by the major cloud vendors and analyzes the services they provide. It also compares them against the solution we developed, called COCOS autoscaling. We simulated the different proposals and fed them with diverse workloads. Obtained results show that COCOS autoscaling outperforms its competitors in most of the cases: it optimizes resource allocation and keeps applications' response times under set thresholds.
autoscaling; cloud computing; containers; control theory; elastic computing
Settore IINF-05/A - Sistemi di elaborazione delle informazioni
Settore INFO-01/A - Informatica
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1227045
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