Cloud Computing has assumed a relevant role in the ICT, profoundly influencing the life-cycle of modern applications in the manner they are designed, developed, and deployed and operated. In this article, we tackle the problem of supporting the design-time analysis of Cloud applications to identify a cost-optimized strategy for allocating components onto Cloud Virtual Machine infrastructural services, taking performance requirements into account. We present an approach and a tool, SPACE4Cloud, that supports users in modeling the architecture of an application, in defining performance requirements as well as deployment constraints, and then in mapping each architecture component into a corresponding VM service, minimizing total costs. An optimization algorithm supports the mapping and determines the Cloud configuration that minimizes the execution costs of the application over a daily time horizon. The benefits of this approach are demonstrated in the context of an industrial case study. Furthermore, we show that SPACE4Cloud leads to a cost reduction up to 60 percent, when compared to a first-principle technique based on utilization thresholds, like the ones typically used in practice, and that our solution is able to solve large problem instances within a time frame compatible with a fast-paced design process (less than half an hour in the worst case). Finally, we show that SPACE4Cloud is suitable to model even microservice-based applications and to compute the corresponding optimized deployment configuration which is compared with a state-of-the art meta-heuristic alternative method, achieving savings between 21 and 85 percent.

Ciavotta, M., Gibilisco, G., Ardagna, D., Di Nitto, E., Lattuada, M., Almeida da Silva, M. (2022). Architectural Design of Cloud Applications: a Performance-aware Cost Minimization Approach. IEEE TRANSACTIONS ON CLOUD COMPUTING, 10(3), 1571-1591 [10.1109/TCC.2020.3015703].

Architectural Design of Cloud Applications: a Performance-aware Cost Minimization Approach

Ciavotta, Michele
Primo
;
2022

Abstract

Cloud Computing has assumed a relevant role in the ICT, profoundly influencing the life-cycle of modern applications in the manner they are designed, developed, and deployed and operated. In this article, we tackle the problem of supporting the design-time analysis of Cloud applications to identify a cost-optimized strategy for allocating components onto Cloud Virtual Machine infrastructural services, taking performance requirements into account. We present an approach and a tool, SPACE4Cloud, that supports users in modeling the architecture of an application, in defining performance requirements as well as deployment constraints, and then in mapping each architecture component into a corresponding VM service, minimizing total costs. An optimization algorithm supports the mapping and determines the Cloud configuration that minimizes the execution costs of the application over a daily time horizon. The benefits of this approach are demonstrated in the context of an industrial case study. Furthermore, we show that SPACE4Cloud leads to a cost reduction up to 60 percent, when compared to a first-principle technique based on utilization thresholds, like the ones typically used in practice, and that our solution is able to solve large problem instances within a time frame compatible with a fast-paced design process (less than half an hour in the worst case). Finally, we show that SPACE4Cloud is suitable to model even microservice-based applications and to compute the corresponding optimized deployment configuration which is compared with a state-of-the art meta-heuristic alternative method, achieving savings between 21 and 85 percent.
Articolo in rivista - Articolo scientifico
cloud computing; cost minimization; Model-driven software development; performance assessment; quality of service; search-based software engineering;
English
11-ago-2020
2022
10
3
1571
1591
reserved
Ciavotta, M., Gibilisco, G., Ardagna, D., Di Nitto, E., Lattuada, M., Almeida da Silva, M. (2022). Architectural Design of Cloud Applications: a Performance-aware Cost Minimization Approach. IEEE TRANSACTIONS ON CLOUD COMPUTING, 10(3), 1571-1591 [10.1109/TCC.2020.3015703].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/304579
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