Objectives and competences
The objectives of this course is for students to be able to demonstrate understanding of theoretical basis of cloud computing, to analyse building blocks for deployment and management and apply and design new variants of algorithms for cloud computing deployment and management.
Content (Syllabus outline)
• Introduction to cloud computing, cloud storage, architecture, cloud service types, deployment models, sample architectures
• Evolution of computer architectures, i.e., distributed/utility/cloud/grid/ computing, cloud platform services
• Private, public, community, and volunteer cloud architectures
• Virtualization: central processing unit, memory, input/output devices, resource management, data centres;
• Programming Models: Distributed Programming for the Cloud, Data-Parallel Architectures with Hadoop MapReduce
• Tools for management and supervision in cloud
• Hardware units in installation of infrastructure as a service, hypervisor
• Service models: infrastructure as a service, platform as a service and software as a service Capacity planning, scheduling and elasticity, HPC architectures and clients, tools to manage HPC
• Advanced algorithm in cloud computing, HPC, parallel and distributed processing of large-scale data
• Cloud software application lifecycle, solutions in practice
• Cloud security: introduction, securing the resources within cloud, securing data, security solutions, etc.
Learning and teaching methods
• Lectures: in lectures, students get to know the theoretical contents of the course. Lectures are conducted as classical lectures in frontal form, interleaved with discussions on practical examples of cloud computing.
• Lab work: in laboratory exercises, students work on individual tasks to learn more about cloud computing.
Intended learning outcomes - knowledge and understanding
• describe, explain, and apply the basic concepts, models, and architectures of cloud computing,
• discuss cloud security and outline technologies for the future of the internet,
• discuss cloud security and outline technologies for the future of the internet,
• write software for algorithms using parallel and distributed computer system models with clustering, virtualization, and tools for cloud management, which process largescale data,
• predict capacity utilization in the cloud and explain cloud task scheduling,
• describe, explain, and apply basic concepts for building data centres and virtualization in the cloud using hypervisor
Intended learning outcomes - transferable/key skills and other attributes
• Communication skills: oral lab work defence, manner of expression at written examination.
• Use of information technology and problem solving: use the concept of cloud storage, and apply the MapReduce programming model.
Readings
• Kai Hwang, Geoffrey C. Fox, Jack J. Dongarra. Distributed and Cloud Computing, From Parallel Processing to the Internet of Things. Morgan Kaufmann. 2012.
• A. Zamuda. Cloud Computing Deployment and Management: A Collection of Exercises and Tasks with Solutions. University of Maribor, University Press. 2020. https://dk.um.si/IzpisGradiva.php?lang=slv&id=77728
• A. Zamuda. Attachments : Computing deployment and management : a collection of exercises and tasks with solutions. Zaključena znanstvena zbirka raziskovalnih podatkov. 2020.
Univezitetna založba Univerze v Mariboru. https://dk.um.si/IzpisGradiva.php?lang=slv&id=77676
• A. Zamuda. Postavitev in upravljanje računalniških oblakov : zbirka vaj in nalog z rešitvami. Maribor : Fakulteta za elektrotehniko,
računalništvo in informatiko. 2019.
https://dk.um.si/IzpisGradiva.php?lang=slv&id=73600
• Barrie Sosinsky. Cloud Computing Bible. Wiley Publishing Inc. 2011.
• Thomas A. Limoncelli, Strata R. Chalup, Cristina J. Hogan. The practice of cloud system administration, Designing and operating large distributed systems. Addison Wesley. 2015.
• Thomas Erl, Robert Cope, Amin Naserpour. Cloud Computing Design Patterns. Prentice Hall; 1st edition. 2015.
• Andreas Wittig, Michael Wittig. Amazon Web Services in Action. Manning Publications. 1st edition. 2015.
• Michael J. Kavis. Architecting the Cloud: Design Decisions for Cloud Computing Service Models (SaaS, PaaS, and IaaS). Wiley; 1st edition. 2014.
Additional information on implementation and assessment The exam may be replaced by written midterm examinations in the weight of 50%.
