Advanced Topics in AI for Networking (Winter 2022/2023)

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Details

Workload/ECTS Credits: 5 ECTS
Module: M.Inf.1222.Mp: Specialization Computer Networks Module Description -or- 3.10: Advanced Topics in Internet Research (II)(ITIS); M.Inf.1223 (new Regulations)
Lecturer: Prof. Xiaoming Fu; Dr. Tingting Yuan
Teaching assistant: [NA]
Time: Wednesday 14:00-16:00
Place: IfI 0.101
UniVZ [1]


Announcements

Please contact me by email:tingting.yuan@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 Tuesday). => 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. Genet: automatic curriculum generation for learning adaptation in networking [2]

2. Multi-resource interleaving for deep learning training [3]

3. NeuroScaler: neural video enhancement at scale [4]

4. Deep Interest Network for Click-Through Rate Prediction [5] [L]

5. Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-Adapting Scheme [6]

6. Routing on Multiple Optimality Criteria[7]

7. Understanding, Detecting and Localizing Partial Failures in Large System Software [8]

8. Understanding Lifecycle Management Complexity of Datacenter Topologies [9] [L]

8. ACC: Automatic ECN Tuning for High-Speed Datacenter Networks [10][A]

10. Seven Years in the Life of Hypergiants’ Off-Nets [11]

11. ATP: In-network Aggregation for Multi-tenant Learning [12]

12. Segcache: a memory-efficient and scalable in-memory key-value cache for small objects[13]

13. MAGE: Nearly Zero-Cost Virtual Memory for Secure Computation [14]

Schedule

W1: Open Talk

W2: Assignment Topics and demo paper reading

W3: Paper ID: (date)

W5: Paper ID: (date)

W7: Paper ID: (date)

!! 25.06 deadline for registration on Flexnow

W9: Rehearsal: Paper ID: (date)

Final Presentation

  • 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)


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