Module COMP4177: NETWORKS AND THEIR STRUCTURE

Department: Computer Science

COMP4177: NETWORKS AND THEIR STRUCTURE

Prerequisites

• COMP2181 Theory of Computation

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To design structured networks to provide the communications fabric of distributed-memory multi-processors, networks-on-chips and data centre networks.
• To introduce the theoretical and practical tools needed to analyse social and technological networks.

Content

• Core aspects of interconnection networks: topology; routing; switching; flow control; packets; technology.
• Graph theory: degree; cuts; bisections; paths; diameter; embeddings; automorphisms; symmetry.
• Topologies: hypercubes; tori; k-ary n-cubes; cube-connected cycles.
• Performance: traffic patterns; throughput; latency; path diversity; packaging; routing algorithms.
• Modelling networks to make comparisons and predictions: random graphs; Milgram's small world experiment; Watts-Strogatz model; Kleinberg model.
• Centrality measures: finding influential nodes in networks; using centrality measures to understand the community structure of networks.
• Epidemics: how contagions spread in networks; models of diffusion; SIR model; epidemic threshold; SIS model.

Learning Outcomes

• On completion of the module, students will be able to demonstrate:
• an awareness of the start-of-the-art in interconnection networks and network science
• an in-depth knowledge of the key design principles of interconnection networks and their relation to current technology
• a detailed knowledge of the structure of real world network and common approaches to building network models

• On completion of the module, students will be able to demonstrate:
• an ability to reason with and apply theoretical methods within interconnection networks and network science
• an ability to implement algorithms within interconnection networks
• an ability to analyse network datasets and build and analyse network models

• On completion of the module, students will be able to demonstrate:
• an ability to critically analyse and evaluate potential solutions within interconnection networks and network science
• an ability to abstract real-world problems within interconnection networks and network science for scientific solution

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures enable the students to learn new material and engage in discussion.
• Formative and summative assessments assess the application of methods and techniques.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Example formative exercises are given during the course.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University