COMP5313/COMP4313—Large Scale Networks S1 2024
Assignment 2
This is an individual assignment.
This assignment is worth 25% of the final mark of the course.
Submit your presentation recording and your final report on Canvas.
Project Proposal Due (Optional): Friday the 12th of April, 23:59 AEST
Presentation Recording and Final Report Due: Week 11, Friday the 10th of May, 23:59 AEST
Task
You can select any one of the following tasks.
1. Programming multiple algorithms for a problem related to the course in C/C++, Java or Python and making a demo of it. Write a report on your findings. For example,
. Take a well known graph algorithm and study its performance. For example you can take several implementations of the algorithm (i.e. in different libraries NetworkX and iGraph or in different programming languages) and benchmark its performance using various datasets. Also, you can compare this with its Big-O complexity and comment whether the implementations match the expected performance.
2. Analyses a real word graph dataset and identify interesting properties of the structure
and the dynamics of the graph. Write a report on your findings. For example,
. Crawl a graph (cf. Twitter lab), select a large graph of your everyday life, or . Take a graph dataset online (e.g., https://canvas.sydney.edu.au/courses/57264/modules/446104)
. Extract properties of the graph, analyse, characterise, visualise and conclude
. Make sure you observe something new (not mentioned by someone else) or choose a novel dataset that was not analysed by someone else
Project Proposal (Optional, NOT marked, but feedback will be given)
Submit one (short) paragraph. Project proposal can contain
. The project option you are choosing and an overall summary of the project
. The datasets you are planning to use or if you are planning to collect your own data, methodology of collecting data
. The tools, libraries, and programming languages you are planning to use
. Any involved algorithms and graph metrics
Recorded Presentation(5 marks)
Whether your choice is to implement algorithms or analyze novel datasets, you need to do a presentation. Your presentation should be between 4 and 8 minutes long. You need to submit a your presentation slides and the recording of your presentation as an mp4 file on Canvas. Presentation video should contain two parts at the same time where one part shows the speaker and the second part shows the slides.
Final Report (20 marks)
Whether your choice is to implement algorithms or analyze novel datasets, you need to write a report of ≥ 4 pages (maximum 6 pages). You need to submit your report as a PDF file as well as your code and dataset as a ZIP file. Cover page and appendix will not be counted towards the page limit.
Marking scheme
Both the report and the presentation should include (it could be short):
1. The context of the study/paper (e.g., social networks, programming languages) and novelty (e.g. dataset that is not been analysed in the past)
2. The problem addressed or the question answered by the study/paper including the mo- tivations for it (why this question/problem is relevant)
3. The methodology (steps taken in terms of experiments of analysis to answer this question or to solve this problem / depth of the methods used)
4. The result (what is the result about and why does it address the problem or answer the question)
5. The conclusion (what this implies, what the limitations, any recent developments are and what the next step would be)
All these 5 points should be clearly stated in both the presentation and the report.