Network Analysis and Dimensioning
Dublin City University
Area of Study
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3
Recommended U.S. Quarter Units5
Hours & Credits
The aim of this module is to introduce the theory and practice of mathematical network analysis and optimisation methods as they apply to the problems of performance analysis of communications protocols, network dimensioning and capacity planning, network architecture design and traffic analysis in modern large-scale data networks, such as optically switched metro and access networks, datacenter and high performance computing interconnects, and femto-macro cell wireless network architectures. Network analysis is essential to understanding and evaluating the fundamental performance properties (e.g. latency, jitter, throughput, packet-drop rate) of complex network architectures and communications protocols. Network dimensioning methods are essential to planning and deploying large-scale networks under given capacity and cost constraints. This module will cover fundamental theory in probability, stochastic processes, queuing theory, graph theory and optimisation methods and apply them to solving various data network design and performance management problems.
1. Derive key results in queuing and teletraffic theory, as apply to the study of communication network performance analysis.
2. Apply methods from probability and queuing theory to modelling of performance-related behaviour of a range of packet-switched and circuit-switched systems and networks.
3. Apply queuing theory equations to calculate system performance measures (e.g. latency, throughput, packet loss) and to perform basic dimensioning of network resources to meet required performance targets.
4. Develop a number of different probabilistic traffic models and determine their applicability to representing different network traffic types.
5. Formulate a range of different network flow and resource dimensioning problems as mathematical optimisation problems.
6. Apply optimisation theory to solving network flow, routing and resource allocation problems.
Courses and course hours of instruction are subject to change.
Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.
ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.
Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.