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Cloud Computing

Code 11481
Year 1
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Informatics
Mode of delivery Face-to-face learning.
Work placements Not applicable.
Learning outcomes The aim of the course is to provide students with a broad and integrative perspective of cloud computing. At the end of the course, students should be able to systematize a vertical approach to the various cloud computing technologies that provide applications and services with greater flexibility, better resource utilization, greater scalability and adaptability, and reduced costs. Students should be able to assess the choices, solutions and commitments involved in configuring and managing cloud systems and should be able to develop scalable and reliable applications and systems for cloud computing.
Syllabus Cloud computing and service models. Comparison of public cloud platforms. Features of grid and cloud platforms. Parallel and distributed programming paradigms. Programming support of Google App Engine. Programming on Amazon AWS. Microsoft Azure programming support. Emerging cloud software environments. Performance of distributed and cloud systems.
Main Bibliography Distributed and Cloud Computing: From Parallel Processing to the Internet of Things, Kai Hwang , Jack Dongarra, Geoffrey C. Fox (Authors), Morgan Kaufmann; 1st edition, 2011, ISBN-13: 978-0123858801, 672 pages.
Cloud Computing: A Hands-On Approach, Arshdeep Bahga, Vijay Madisetti (Authors), Vijay Madisetti, 2014, ISBN-13: 978-0996025508, 456 pages.
Guide to Reliable Distributed Systems: Building High-Assurance Applications and Cloud-Hosted Services, Kenneth P Birman (Author), Springer, 2012, ISBN-13: 978-1447124153, 730 pages.
Planned learning activities and teaching methods The theoretical lectures of this curricular unit are based on the presentation of theoretical material. The practical lectures of this curricular unit consist of the design, implementation, configuration and testing of experimental solutions to assigned practical problems.
Metodologias de Ensino e Critérios de Avaliação Teste de avaliação de conhecimentos/Exame (sem consulta): 40%.
Trabalho de síntese: 15%.
Projetos laboratoriais ou de campo: 45%
Language Portuguese. Tutorial support is available in English.
Last updated on: 2014-08-07

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