A Modelling Language for Defining Cloud Simulation Scenarios in RECAP Project Context
1. Reliable Capacity Provisioning and Enhanced
Remediation for Distributed Cloud Applications
http://recap-project.eu recap2020
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020
RESEARCH AND INNOVATION PROGRAMME UNDER GRANT AGREEMENT NUMBER 732667
A Modelling Language for Defining Cloud Simulation
Scenarios in RECAP Project Context
Cleber Matos de Morais, Patricia Takako Endo, Sergej Svorobej, Theo Lynn
Dublin City University (DCU), Ireland
3. Motivation
• Dynamic edge/fog/cloud infrastructure are very complex and
specific and we need to run fast and flexible simulation to make
management decisions;
• To simulate these scenarios, we need an unique simulation
configurations file with scenarios requirements; and
• Simulation configuration are time consuming and require
experienced staff with specialist expertise.
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4. Approach
• Model an abstraction that can be easily reconfigured using the
Model-driven Development methodology;
• Define abstract entities that should be mapped to the model and
its relations;
• Create constrains rules to the visual modelling that implements a
great variety of business rules;
• Automatically generate outputs that fit the RECAP simulation needs.
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5. Theories
• Model-driven Development (MDD) is an evolution of the software
diagrams and software development methodologies that deal with
high level abstractions to define their system requirements, and
then automatically generate code;
• To make use of MDD, it is necessary to define a Domain Specific
Modeling Language (DSML) to describe the system requirements
that often feature a special graphical notation (concrete syntax) that
helps to improve the clarity and comprehensibility of models.
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10. In a nutshell…
• An application of the Model-driven Development methodology;
• Easy configuration and flexibility to change during the business
analysis process;
• High level solution that do not require a configuration specialist;
• Build-in business model rules;
• Better documentation and increased quality of the simulation
parameters set-up.
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11. THANK YOU
http://recap-project.eu recap2020
RECAP Project ■ H2020 ■ Grant Agreement #732667
Call: H2020-ICT-2016-2017 ■ Topic: ICT-06-2016
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020
RESEARCH AND INNOVATION PROGRAMME UNDER GRANT AGREEMENT NUMBER 732667
patricia.endo@dcu.ie,
cmorais@gmail.com