Spring 2025
Credits: 3
Meeting Times: Tuesday/Thursday, 3:00pm – 4:15pm
Meeting Location: 1212 Engineering Building II
Assignment submission: Moodle
Message board: Piazza

 

Instructor Information

  • Xiaohui (Helen) Gu
  • Office Hours: Tues/Thurs 3:00pm – 4:15pm  at EBII  3274
  • Email : xgu AT ncsu.edu

Teaching Assistants/Graders

  • Tanvin Kalra (Grader)
  • Email : tkalra AT ncsu.edu

 

Course Objectives

This course explores design and implementation principles in modern distributed systems. In particular, the course will emphasize on recent techniques used by real-world distributed systems such as cloud systems, enterprise data center, and peer-to-peer file sharing (e.g., BitTorrent). Students will learn the state of the art in distributed system architectures, algorithms, and performance evaluation methodologies. Topics include canonical distributed concepts such as remote procedure call, distributed objects, replication, distributed system security, consensus protocol, and recent distributed system technologies such as peer-to-peer, grid, autonomic computing, distributed massive data processing/Google map-reduce, system machine learning,  distributed system debugging, multi-core systems, distributed virtualization. On completing this course, the student should be able to the following:

  • Identify research problems and challenges in distributed systems, (assessed by review and presentation);
  • List the state-of-art tools and techniques for addressing research problems and challenges in distributed systems (assessed by review and presentation);
  • Develop and implement new ideas to solve open problems in  distributed systems (assessed by project);
  • Conduct technical reviews, technical writing, and technical presentations (assessed by review, project, paper, presentation).

Text Books

There are no assigned textbooks for this course. Topics will be covered during in-class lectures, and through course notes made available on this web page.
Links to the supplementary material in the form of research papers related to each topic are included in this syllabus [Course Syllabus]. PDF for most papers is available through the NCSU library web site, which has full-text access to most recent ACM and IEEE journals and conferences. A number of supplemental distributed system textbooks are also available:
Distributed Systems: Concepts and Design, (4th Edition), G. Coulouris, J. Dollimore, and T. Kindberg
Distributed Systems (2nd Edition), Sape Mullender
Distributed Systems: Principles and Paradigms, Andrew S. Tanenbaum, Maarten van Steen

Course Description

Distributed systems have become the fundamental computing infrastructure for many important real-world applications such as Internet search engine, media streaming servers, online file sharing, information analytics, and scientific exploration. This course explores design and implementation principles in modern distributed systems. In particular, the course will emphasize on recent techniques used by real-world distributed systems such as peer-to-peer file sharing (e.g., BitTorrent), enterprise data center, and Internet search engine (Google). Students will learn the state of the art in distributed system architectures, algorithms, and performance evaluation methodologies. Topics include i) traditional distributed computing concepts (e.g., distributed objects, middleware, replication, distributed system security, and consensus protocol); and ii) recent emergent distributed system techniques such as peer-to-peer systems, massive data processing, Grid, and autonomic computing. Students will have opportunities to not only learn the common design methodology of many important distributed systems, but also gain hands-on experience through project implementations. The majority of course materials will be drawn from classic papers and current state-of-the-art work. The instructor will lecture for the first half of the semester and students will present papers and projects in the second half of the semester. Students will read and review papers ahead of time, participate in class discussions, present at least one research topic during the course, and do a term project individually or in a two-member team. Students will also write a paper (as well as review other students’ papers) describing their project and present their work at the end of the course, in a “conference” format designed to give students an experience similar to that of participating in a professional conference.

Prerequisites

CSC501 or equivalent. Programming in C++ or Java in Unix environment. If you are not sure whether you can attend this course, please consult the instructor.

Tentative Grading Policy

Written reviews 20%, class participation 30% (presentation: 20%, discussion: 10%), project 50% (proposal writeup 5%, proposal presentation 5%, Project MidReview Presentation  5%, demo 15%, final presentation 10%, Final write-up 10%)

Late policy

Calculated by the time recorded in the assignment emails received to the instructor. Students will lose 25% for each 24-hour period they are late on reviews, project, or paper.

Paper Review

Review guidelines: Provide a paragraph of summary about the paper, a paragraph of 2-3 strong points of the paper (i.e., Why the paper should be accepted), a paragraph of 2-3 weak points of the paper (i.e., why the paper should be rejected),  brainstorming ideas for developing new research ideas related to the work described in the paper(optional).

Project

Both project proposal and final report should follow typical paper requirements using ACM Double-Column Paper format. The project proposal should include abstract, introduction, proposed approaches, and related work. The final project report should include a full paper content including abstract, introduction, design and algorithms, experiment evaluation, related work, and conclusion. We will organize a mini-conference for the students to present their project work. Three best papers will be selected during the mini-conference.

Class Schedule (Tentative)

 W  Date Topic Assigned Readings Assignments
1 1/7

Introduction [slides]
  • Chapter 1, Distributed Systems: Concepts and Design
 Investigate your term project idea and do preparation for it. A list of candidate project topics will also be provided to you on the class. Talk to the instructor about your project idea and talk to other students in forming a two-three members group. Email the instructor to setup the appointment.

1/13 midnight: Review due for
1/9 Replication [slides]
2 1/14 Project Testbed   Investigate your term project idea and do preparation for it. Talk to the instructor about your project idea and talk to other students in forming a group if you would like to work in a group.

1/20 midnight: Review due for

Sunday midnight (1/19): Paper presentation signup due. Please send an email to the TA to bid three papers in the list below and list your choices in decreasing order. You will be allocated with one paper to present based on the FCFS policy and paper availability.
1/16 Project Testbed [slides]  
3 1/21  Project Testbed

 

 1/27 midnight: Review due for
1/23 Consensus Protocol
4 1/28 Consensus Protocol  
1/30 Consensus Protocol
5 2/4 Autonomic Computing [slides]

 

 2/10 midnight: Project proposal due
2/6

Overlay Networks [slides]
  • D. Andersen and H. Balakrishnan and F. Kaashoek and R. Morris, Resilient Overlay Networks, Proc. 18th ACM SOSP, 2001.
  • Y. Chu and S. G. Rao and S. Seshan and H. Zhang, A Case For End System Multicast, IEEE Journal on Selected Areas in Communication (JSAC), Special Issue on Networking Support for Multicast”, 2002.
6 2/11 Wellness Day (No classes)  
2/13

Peer-to-Peer Systems

[slides]
  •  

2/17 midnight: Reviews due
7 2/18 Big Data [slides] 2/24 midnight: Reviews due
2/20 System Research Methodology [slides]

 

  •  
8 2/25 Project Proposal Presentation
  1. Atomic Transactions in Distributed Key Value Store – Sachin R Doddaguni, Samarth Mahesh Shetty
  2. Autonomous Agentic RAG with Distributed Vector Databases for Scalable Information Retrieval – Tural Mehtiyev, Anirudh Kaluri, Sagar Dama
  3. Distributed Hash Table (DHT) using Chord – Apurv Choudari, Harikrishnan Venkatesh, Kruthik Jonnagaddala
  4. Improving Chunking Algoritham for BeeGFS – Aryan Gupta, Jayesh Bhagyesh Gajbhar, Tanishq Virendrabhai Todkar
  5. Leveraging Self-Supervised Hybrid Learning for Container Security in Kubernetes: A Detection and Response Framework – Sumeet Bapurao Khillare, Shanmukh Pawan Moparthi, Chirag Bheemaiah Palanganda Karumbaiah
  6. LogPress: Optimized Compression and Retrieval of Unstructured Logs – Neel Dudheliya, Pranav Jibhakate, Tanay Gandhi 
  7. SPHERE: Scalable Proactive Handling for Efficient Resource Expansion – Kashika Malick, Rajat Chandak, Shubh Nisar
 3/3 midnight: Reviews due
2/27  Student presentation
9 3/4 Student presentation

 

 No paper reading assigned. You should spend time on your term projects.
3/6 Student presentation

10

3/11

 Spring Break
  • No Class
 No paper reading assigned. You should spend time on your
term projects.

3/13

 Spring Break
  • No Class
11 3/18 Student presentation No paper reading assigned. You should spend time on your term projects.
3/20  Project MidReview

 
12 3/25 Project MidReview   No paper reading assigned. You should spend time on your term projects.
3/27 Student presentation
13 4/1 Student presentation No paper reading assigned. You should spend time on your term projects.
4/3 Student presentation
14 4/8 Student presentation No paper reading assigned. You should spend time on your term projects.
4/10 Student presentation
15 4/15 Student presentation No paper reading assigned. You should spend time on your term projects.
4/17 Project Demo

 
16 4/22 Project Demo  

April 29th midnight: Final project report due, project source code and document due

Your project source code and document submission should be a single zip file. The zip file should include your system source code including all other dependent packages, the experimental subjects used in the project report, instructions on how to set up and use the system to reproduce the experimental results, and other documents that help others understand your tool and source code.
4/24

Project presentation 

1pm-5:30pm

  
17      

Suggested Topics for Student Presentations

(You can suggest to the instructor the papers that are not in this list but you would like to present):

Please check below for your assigned paper.

AI-Driven Distributed System Management

  1. “ClearCausal: Cross Layer Causal Analysis for Automatic Microservice Performance Debugging“,Olufogorehan Tunde-Onadele, Feiran Qin, Xiaohui Gu, Yuhang Lin, 5th IEEE International Conference on Autonomic Computing and Self-Organizing Systems – Apurv Choudhari (apchoudh)
  2. Jingzhu He, Ting Dai, Xiaohui Gu, and Guoliang Jin, “HangFix: Automatically Fixing Software Hang Bugs for Production Cloud Systems“, Proc. of ACM Symposium on Cloud Computing (SOCC), Renton, WA, October, 2020, pp. 344-357. – Tanishq Virendrabhai Todkar (ttodkar)
  3. Ting Dai, Jingzhu He, Xiaohui Gu, Shan Lu, and Peipei Wang, “ DScope: Detecting Real-World Data Corruption Hang Bugs in Cloud Server Systems“, Proc. of ACM Symposium on Cloud Computing (SOCC), Carlsbad, CA, October, 2018. – Jayesh Bhagyesh Gajbhar (jgajbha)
  4. Daniel Dean, Hiep Nguyen, Xiaohui Gu, Hui Zhang, Junghwan Rhee, Nipun Arora, Geoff Jiang, PerfScope: Practical Online Server Performance Bug Inference in Production Cloud Computing Infrastructures“, Proc. of SOCC 2014. – Kashika Malick (kmalick)
  5. Hiep Nguyen, Zhiming Shen, Yongmin Tan, Xiaohui Gu,”FChain: Toward Black-box Online Fault Localization for Cloud Systems”, Proc. of ICDCS 2013. – Shubh Nisar (snisar)
  6. Daniel Dean, Hiep Nguyen, Xiaohui Gu, “UBL: Unsupervised Behavior Learning for Predicting Performance Anomalies in Virtualized Cloud Systems”, Proc. of ACM International Conference on Autonomic Computing (ICAC), San Jose, CA, September, 2012. – Rajat Girish Chandak (rchanda3)
  7. “If At First You Don’t Succeed, Try, Try, Again…? Insights and LLM-informed Tooling for Detecting Retry Bugs in Software Systems“, Bogdan Alexandru Stoica, Utsav Sethi , Yiming Su , Cyrus Zhou, Shan Lu, Jonathan Mace, Madan Musuvathi, Suman Nath, ACM SOSP 2024 | November 2024 – Tural Mehtiyev (tmehtiy)

Cloud Computing & Data Center & Big Data

  1. Mike Chow, ServiceLab: Preventing Tiny Performance Regressions at Hyperscale through Pre-Production Testing, Proc. of OSDI 2024 – Harikrishnan Venkatesh (hvenkat2)

  2. Rui Wang, et al,, μSlope: High Compression and Fast Search on Semi-Structured Logs, Proc. of OSDI 2024 – Anirudh Kaluri (akaluri)
  3. Y. Sheng et al., Fairness in Serving Large Language Models, Proc. of OSDI 2024 – Samarth Shetty (sshett22)
  4. Philipp Moritz et al., Ray: A Distributed Framework for Emerging AI Applications, Proc. of OSDI 2018 – Tanay Gandhi (tgandhi)
  5. Martín Abadi et al., TensorFlow: A System for Large-Scale Machine Learning, Proc. of OSDI 2016. – Chirag Bheemaiah Palanganda Karumbaiah (cpalang)
  6. Hiep Nguyen, Zhiming Shen, Xiaohui Gu, Sethuraman Subbiah, John Wilkes,”AGILE: elastic distributed resource scaling for Infrastructure-as-a-Service“, Proc. of USENIX International Conference on Autonomic Computing (ICAC), San Jose, CA, June, 2013. – Sachin R Doddaguni (srdodda)
  7. Zhiming Shen, Sethuraman Subbiah, Xiaohui Gu, and John Wilkes, CloudScale: Elastic Resource Scaling for Multi-Tenant Cloud Systems, Proc. of ACM SOCC 2011. – Kruthik Jonnagaddala Thyagaraja (kjonnag)
  8. Xiaohui Gu, Klara Nahrstedt, A Scalable QoS-Aware Service Aggregation Model for Peer-to-Peer Computing Grids, Proc. of IEEE International Symposium on High Performance Distributed Computing (HPDC 2002) – Aryan Gupta (agupta72)

Distributed Systems Security

  1. Olufogorehan Tunde-Onadele, Yuhang Lin, Xiaohui Gu, and Jingzhu He, “Understanding Software Security Vulnerabilities in Cloud Server Systems“, Proc. of the 10th IEEE International Conference on Cloud Engineering (IC2E), Pacific Grove, CA, September, 2022 – Pranav Arvind Jibhakate (pjibhak)
  2. Yuhang Lin, Olufogorehan Tunde-Onadele, Xiaohui Gu, Jingzhu He, and Hugo Latapie, SHIL: Self-Supervised Hybrid Learning for Security Attack Detection in Containerized Applications“,
    Proc. of the 3rd IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), Los Angeles, CA, September, 2022 – Sumeet Bapurao Khillare (skhilla)
  3. Yuhang Lin, Olufogorehan Tunde-Onadele, and Xiaohui Gu,“CDL: Classified Distributed Learning for Detecting Security Attacks in Containerized Applications“, Proc. of Annual Computer Security Applications Conference (ACSAC), Austin, TX, December, 2020. – Neel Dudheliya (ndudhel)
  4. Olufogorehan Tunde-Onadele, Yuhang Lin, Jingzhu He, and Xiaohui Gu, “Self-Patch: Beyond Patch Tuesday for Containerized Applications“, Proc. of IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), Washington, DC, August, 2020, pp. 21-27. – Sagar Dama (sudama)
  5. Rui Shu et al., A Study of Security Vulnerabilities on Docker Hub, Proc. of CODASPY 2017 – Shanmukh Pawan Moparthi (smopart2)

Academic Integrity

The university provides a detailed policy on academic integrity. This policy can be found in the Code of Student Conduct. It is understood that when you submit your homework, you are implicitly agreeing to the university honor pledge: “I have neither given nor received unauthorized aid on this test or assignment.”

Academic dishonesty (e.g., cheating or plagiarism) will not be tolerated under any circumstances. If you are having difficulty with any part of the course material, please see me as soon as possible. I will do everything I can to help you with any course-related problems you may be having. If you are found to be guilty of academic dishonesty, however, I will then do everything I can to see that you are punished as forcefully as possible. This may include asking to have you suspended or expelled from the course, the program, and/or the university. At a minimum, you will receive -50% for the assignment in question, and your name will be placed on record with the university as having committed an academic offence. Multiple offences during your academic career will result in suspension or expulsion from the university. I take absolutely no pleasure in pursuing cases of academic misconduct, and would ask that you please do not put me in this position.

Students With Disabilities

All effort will be made to ensure that no students with disabilities are denied any opportunity to successfully complete this course. If you have specific requirements that need to be addressed, please contact me immediately. Possible changes can include (but are not necessarily limited to) rescheduling classes from inaccessible to accessible buildings, or providing access to auxiliary aids such as tape recorders, special lab equipment, or other services such as readers, note takers, or interpreters. This may also include oral or taped tests, readers, scribes, separate testing rooms, or extension of time limits.

Lab Safety Issues

None.

Pass-Through Costs

None.