2024/25 Taught Postgraduate Module Catalogue

COMP5123M Cloud Computing Systems

15 creditsClass Size: 230

Module manager: Prof Karim Djemame
Email: k.djemame@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2024/25

This module is not approved as an Elective

Module summary

Driven by trends in the consumer Internet, cloud computing has become the de facto standard to consume and deliver IT services. The cloud computing model builds on the maturation of the Web, combining rapid scalability, proliferation of the Internet and Internet connected devices, unprecedented self-service and the emergence of elegant web-based applications. Data is becoming larger, more complex data sets, especially from new data sources such as the Internet of Things. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address new business problems. The module aims to develop a practical understanding of methods, techniques and architectures needed to build big data systems, so that knowledge may be extracted from large heterogeneous data sets. This module is supported by the strong research interest and expertise in cloud and related technologies within the School of Computing and develops expertise in cloud computing and big data systems by giving the students the skills and knowledge to design, build and extend the Internet infrastructure and to design a variety of applications

Objectives

On completion of this module, students should be able to:

- Demonstrate an understanding of cloud computing techniques and technologies;

- Demonstrate an understanding of the contexts in which big data systems are applied;

- Identify the paradigms that determine the requirements, capabilities and performance of Cloud systems;

- Design a high-level framework of a Cloud architecture;

- Use a range of middleware tools to implement a cloud application;

- Reason about the significance of the new directions that Cloud computing is taking.

Learning outcomes
On completion of the year/programme students should have provided evidence of being able to:

- to demonstrate in-depth, specialist knowledge and mastery of techniques relevant to the discipline and/or to demonstrate a sophisticated understanding of concepts, information and techniques at the forefront of the discipline;

- to exhibit mastery in the exercise of generic and subject-specific intellectual abilities;

- to demonstrate a comprehensive understanding of techniques applicable to their own research or advanced scholarship;

- proactively to formulate ideas and hypotheses and to develop, implement and execute plans by which to evaluate these;

- critically and creatively to evaluate current issues, research and advanced scholarship in the discipline.

Syllabus

Definitions of cloud systems; Grids versus Clouds; Cloud application challenges; Taxonomy of cloud systems; Cloud services; Virtualisation; Virtual Infrastructure Management; Virtual machines, containers and unikernels; Disaggregated computing; Serverless architectures; Definitions of big data, the five 'Vs' (Volume, Velocity, Variety, Veracity & Value). MapReduce; Energy efficiency; Service level agreements; Cloud use cases; Programming models; Data-intensive information processing; Quality of Service; Cloud computing future trends; Security and trust; ubiquitous clouds and the Internet of things, cloud economy, edge computing. Exascale computing.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	20	1.00	20.00
Practical	10	1.00	10.00
Private study hours			120.00
Total Contact hours			30.00
Total hours (100hr per 10 credits)			150.00

Opportunities for Formative Feedback

Practical exercises and online MCQs on Minerva/Gradescope.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	Coursework	20.00
In-course Assessment	MCQ Test	20.00
Total percentage (Assessment Coursework)		40.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams

Exam type	Exam duration	% of formal assessment
Open Book exam	2 hr 00 mins	60.00
Total percentage (Assessment Exams)		60.00

This module will be reassessed by open book exam.

Reading list

There is no reading list for this module

Last updated: 25/09/2024 09:18:38

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