You need to activate javascript for this site.
Menu Conteúdo Rodapé
  1. Home
  2. Courses
  3. Computer Science and Engineering
  4. Cloud Computing

Cloud Computing

Code 11481
Year 1
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Informatics
Entry requirements Students must have ground knowledge on networks, computer programming and software engineering.
Mode of delivery Face-to-face learning.
Work placements Not applicable.
Learning outcomes The aim of the course is
a) to provide students with a broad and integrative perspective of cloud computing.

At the end of the course, students should
b) be able to systematize a vertical approach to the various cloud computing technologies
c) that provide applications and services with greater flexibility, better resource utilization, greater scalability and adaptability, and reduced costs.
d) Students should be able to assess the choices, solutions and commitments involved in configuring and managing cloud systems and
e) 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.
Teaching Methodologies and Assessment Criteria
Teaching Method:?
1. Expository method?
2. Supervised group work
3. Self-learning
4. Peer learning
5. Project work

written test / Exam (without documentation support): 40%.
Synthesis work: 15%.
Field or Laboratory projects: 45%

Language Portuguese. Tutorial support is available in English.
Last updated on: 2014-08-07

The cookies used in this website do not collect personal information that helps to identify you. By continuing you agree to the cookie policy.