COMP4227: Distributed Network Computing and Algorithms

• COMP2181 Theory Of Computation

• None

• None

• To introduce students to network based distributed computing paradigms and algorithm design concepts.
• To equip students with the ability to design and analyse efficient distributed algorithms and data structures.

• Network abstracted as a graph.
• Distributed computing models and analysis: LOCAL, CONGEST . . .
• Fundamental and classic distributed algorithms: Flooding, Leader Election, etc.
• Centralised to distributed via classic graph problems: Maximal Independent Set (MIS), Colouring, Matching, Minimum Spanning Tree (MST), etc.
• (Advanced) Topics from the following:
• (Secure) Computation despite faults: Fault-tolerant distributed computation despite attacks and/or edge/node insertions/deletions.
• Byzantine fault-tolerance: Foundations of Blockchain/Cryptocurrency.
• Autonomous systems: Self-stabilization, Self-healing, Mobile robots.
• Algorithm complexity and general design techniques: Network Decomposition and Graph Shattering.

Subject-specific Knowledge:

• On completion of the module, students will be able to demonstrate:
• An understanding of computing, abstraction, and algorithms for networks and decentralised systems;
• An understanding of formal concepts for designing and analysing distributed algorithms;
• An understanding of fundamental distributed algorithms and distributed variants of classic graph problems;
• An understanding of advanced distributed concepts such as fault-tolerant algorithms.

Subject-specific Skills:

• On completion of the module, students will be able to demonstrate:
• An ability to abstract real-world problems and network architectures to provide solutions by specific distributed algorithms;
• Appreciating real world constraints and an ability to reason about decentralised and distributed systems;
• An ability to design distributed solutions (algorithms) and analyse accordingly.

Key Skills:

• On completion of the module, students will be able to demonstrate:
• An ability to abstract problems to devise computational solutions;
• An ability to reason about multi-agent, decentralised and distributed systems and networks;
• A scientific approach to algorithm and system design.

• Lectures enable the students to learn new material relevant to distributed systems, distributed computing and distributed algorithms in various scenarios.
• Summative assessments assess the understanding of distributed systems, distributed computing, distributed algorithms, and the ability to design and analyse such algorithms.

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