Advanced Topics in AI for Networking (Summer 2023)

From NET Wiki
Jump to navigation Jump to search

Details

Workload/ECTS Credits: 5 ECTS
Module: M.Inf.1123
Lecturer: Prof. Xiaoming Fu; Dr. Tingting Yuan; Wenfang Wu;
Teaching assistant: [NA]
Time: Thursday 14:00-16:00


Announcements

Please contact me by email: wenfang.wu@cs.uni-goettingen.de if you have any questions.

Course Overview

The purpose of this seminar is to discuss some advanced topics in computer networks. This course is a theory-oriented research seminar (5 ECTS, 2 SWS), held on a weekly base and comprises the following components:

  • Weekly Presentation + Weekly Paper Reading and Discussion 40%
  • Final Presentation 30%
  • Final Report 30%

The material in the seminar is mainly drawn from the research literature in top journals/conferences, like ToN,TMC, TPDS, SIGCOMM, SIGMETRICS, INFOCOM, MOBICOM, MOBIHOC, WWW, CoNEXT.

Requirements

  • Each participant is required to read the assigned paper before the seminar and prepare the review of the paper, which should include the following parts:
    • Summary of the paper
    • Pros and cons of the paper (your conclusion)
    • NOTE!! Every participant should provide the paper review BEFORE the seminar (23:59 on Wedesday). => the review form is available at [Paper_Review_Form_ATCN_WS201112.doc]
  • During each weekly seminar, one participant is assigned for presenting the paper (each presentation lasts for ~20 minutes) and the list of pros and cons are discussed by all the participants.
  • In the middle of the semester, everyone is requested to prepare:
    • Final report: Essay (5~6 pages, double columns, IEEE format) for your chosen research topic, which contains a comprehensive literature survey + a detailed discussion of some key enabling technologies
    • Final presentation: each presentation lasts for ~20 minutes, plus ~10 minutes Q&A

List of Papers

1. Learning for Crowdsourcing: Online Dispatch for Video Analytics with Guarantee [1]

2. Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition [2]

3. CASVA: Configuration-Adaptive Streaming for Live Video Analytics [3]

4. Batch Adaptative Streaming for Video Analytics [4]

5. FlexPatch: Fast and Accurate Object Detection for On-device High-Resolution Live Video Analytics [5]

6. AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning [6]

7. RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation [7]

8. Deep Reinforcement Learning-Based Control Framework for Radio Access Networks [8]

9. NeuLens: Spatial-based Dynamic Acceleration of Convolutional Neural Networks on Edge [9]

10. FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [10]

11. TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers [11]

12. Mousika: Enable General In-Network Intelligence in Programmable Switches by Knowledge Distillation [12]

13.

14.

Schedule

W1: Open Talk (13.4)

W2: Assignment papers

W4: Paper ID:

W...

W10: Rehearsal:

!! xx.xx deadline for registration on Flexnow

Final Presentation (xx.07)

  • Paper Title:
  • Paper Title:

Report deadline

Final Presentations & Report

  • Final Registration in FlexNow: To Be Announced (TBA).


  • Final Presentation:
    • Each for ~20 minutes, plus ~10 minutes Q&A


  • Final Presentation Slots:
    • To Be Announced (TBA)


Retrieved from "https://wiki.net.informatik.uni-goettingen.de/index.php?title=Advanced_Topics_in_AI_for_Networking_(Summer_2023)&oldid=8015"