2015/16 Taught Postgraduate Module Catalogue
ELEC5420M Communication Network Design
15 creditsClass Size: 65
Module manager: Prof. Jaafar Elmirghani
Email: j.m.h.elmirghani@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2015/16
This module is not approved as an Elective
Objectives
To teach the student the basic models, algorithms and theories of communication networks design;- To understand linear programing and meta heuristics as tools for communication networks design and analyse case studies and implementation scenarios;
- To understand dynamic network design by covering topics such as dynamic programming, game theory, Markov chains and queuing theory.
Learning outcomes
On completion of this module, students should be able to:
- understand the underlying principles of communication network design and optimisation;
- construct basic network optimisation formulations with cost functions and constraints and solve these formulations;
- appreciate future developments and design requirements (e.g. core of the Internet, wireless networks, access networks).
- understand the need for meta heuristics and be able to explain a selection (e.g. Tabu search vs genetic algorithms);
- understand the basic principles of dynamic network designs, for example queuing performance and hence perform delay and packet loss evaluations and compare and contrast network designs and performance;
- perform dynamic programming analysis and construct game theory network optimisation formulations;
- use the theoretical and technical content of the module to assess the limitations and possibilities of communication networks
Syllabus
1. Network optimization
-Linear programming
-Linear programming solutions using simplex algorithm
-Duality and sensitivity analysis
-Network optimization models: shortest path, minimum spanning tree, maximum flow, minimum cost
-Example in communication networks
2. Meta heuristics and programming
-Integer programming: branch-and-bound technique
-nonlinear programming
-Tabu search
- Genetic algorithms
-Use of meta heuristics in network design
3. Dynamic network design
-Dynamic programming
-Game theory: two-person, zero-sum game, games with mixed strategies, graphical solution procedure, solving by linear programing
-Markov chains: stochastic Processes, Chapman-Kolmogorov equations, states of a Markov chain
-Queuing theory: birth-and-death, priority-discipline queuing models, queuing networks, model with non-exponential distributions
-Evaluation of dynamic performance of typical communication networks
Teaching methods
Delivery type | Number | Length hours | Student hours |
Example Class | 4 | 1.00 | 4.00 |
Class tests, exams and assessment | 1 | 4.00 | 4.00 |
Lecture | 10 | 2.00 | 20.00 |
Private study hours | 122.00 | ||
Total Contact hours | 28.00 | ||
Total hours (100hr per 10 credits) | 150.00 |
Private study
Directed reading, working through set problems, performing software simulations provided by lecturer and developing his/her own.Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
In-course Assessment | In-semester assignment | 20.00 |
Total percentage (Assessment Coursework) | 20.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
Exam type | Exam duration | % of formal assessment |
Standard exam (closed essays, MCQs etc) | 3 hr 00 mins | 80.00 |
Total percentage (Assessment Exams) | 80.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
There is no reading list for this moduleLast updated: 17/08/2015
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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