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CSC8103 : Distributed Algorithms

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Paul Ezhilchelvan
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System


Distributed algorithms are the foundation on which system services are built. The aim of the module is to cover core algorithms by concentrating on three key attributes that are very significant in building responsive applications: processing and communication delays and component failures.

Outline Of Syllabus

Preliminaries: Synchronous and Asynchronous communication models, precedence relations, non- deterministic computations and execution configurations, basics of tree structures, and basics of cryptography.

Fundamental Algorithms: Wave and Election Algorithms for trees, rings, and arbitrary topological structures.
Example applications on Routing Algorithms and e-auction sites.

Algorithms in e-Commerce: Fair Exchange Algorithms. On-line and Off-line algorithms. Contract Exchange Applications.

Algorithms for Distributed Data Management: Database Commit Protocols: 2-phase and 3-phase protocols. The requirements and the limitations of commit protocols.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture211:0021:00In-person lectures (20)
Guided Independent StudyAssessment preparation and completion120:0020:00Exam and preparation
Guided Independent StudyAssessment preparation and completion201:0020:00Problem solving exercise
Scheduled Learning And Teaching ActivitiesSmall group teaching41:004:00PiP for feedback on Formative Coursework
Structured Guided LearningStructured non-synchronous discussion100:305:00Support for coursework and deep learning
Guided Independent StudyIndependent study301:0030:00Background reading
Teaching Rationale And Relationship

Lecture materials will introduce the learning material and demonstrate the key concepts by examples. Students are expected to follow-up within a few days by re-reading and annotating lecture notes to engage in deep learning. They will also be helped in this process through Structured non-synchronous discussions.

This is a very fundamental subject and it is therefore important that the learning materials are supported by plenty of examples and, if possible, by the animation software that interactively explains the workings of the algorithms. Students are expected to spend time on working out examples in their independent study hours and, in case of difficulties, raise questions during the structured non-synchronous discussion sessions which are generously fixed to be 10 in total.

Students aiming for 1st class marks are expected to widen their knowledge beyond the content of lecture notes through background reading.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Description Length Semester When Set Percentage Comment
Written Examination901A100Closed book exam
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Prob solv exercises1MProblem Solving Exercises: (set end of 6th and 9th lectures)
Assessment Rationale And Relationship

The assessment (both summative and formative), assess the knowledge of techniques and theory presented in lectures and also application skills in the context of a more realistic and open-ended problems.

Reading Lists