Authors:
Eden Dosciatti
1
;
Marcelo Teixeira
1
;
Richardson Ribeiro
1
;
Marco Barbosa
1
;
Fábio Favarim
1
;
Fabrício Enembreck
2
and
Dieky Adzkiya
3
Affiliations:
1
Federal University of Technology-Paraná, Brazil
;
2
Pontificial Catholical University-Paraná, Brazil
;
3
Delft University of Technology, Netherlands
Keyword(s):
Modeling, Simulation, Resources Planning, Performance, Availability.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Enterprise Resource Planning
;
Enterprise Software Technologies
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Operational Research
;
Scheduling and Planning
;
Simulation
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Software Engineering
Abstract:
Anticipating resources consumption is essential to project robust database infrastructures able to support transactions to be processed with certain quality levels. In Database-as-a-Service (DBaaS), for example, it could help to construct Service Level Agreements (SLA) to intermediate service customers and providers. A proper database resources assessment can avoid mistakes when choosing technology, hardware, network, client profiles, etc. However, to be properly evaluated, a database transaction usually requires the physical system to be measured, which can be expensive an time consuming. As most information about resource consumption are useful at design time, before developing the whole system, is essential to have mechanisms that partially open the black box hiding the in-operation system. This motivates the adoption of predictive evaluation models. In this paper, we propose a simulation model that can be used to estimate performance and availability of database transactions at d
esign time, when the system is still being conceived. By not requiring real time inputs to be simulated, the model can provide useful information for resources planning. The accuracy of the model is checked in the context of a SLA composition process, in which database operations are simulated and model estimations are compared to measurements collected from a real database system.
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