1. CS/CE/TE 6378 Advanced Operating Systems
Course Overview
CS/CE/TE Advanced Operating Systems

2. Professor Introduction
Dr. Liu
Assistant Professor of Computer Science
Director of the Real-Time & Embedded Systems Lab
Research interests:
Real-Time & Embedded Systems
Batter-Powered Cyber-Physical Systems
GPGPU
Mobile and Cloud Computing
Course Overview

3. Office Hours Location: ECSS 4.211 Hours: Friday 8am – 10am
Schedule appointments by
Course Overview

4. Distributed Systems Distributed System:
“A distributed system is one in which the failure of a computer you didn’t even know existed can render your own computer unusable.”
Course Overview > Distributed Systems

5. Distributed Systems What’s a distributed system?
A set of nodes, connected by a network, which appear to its users as a single coherent system.
Course Overview > Distributed Systems

6. Examples Internet Automatic banking Telecommunications
Industrial control systems
Supercomputers
Multiplayer video games
Course Overview > Distributed Systems

7. Advantages Resource sharing (e.g., Internet)
Reliability (e.g., industrial control systems)
Performance (e.g., supercomputing)
Expandability (e.g., multiplayer video games)
Course Overview > Distributed Systems

8. Why Study Distributed Systems?
It is important and useful
Societal importance
Internet
Small devices (mobiles, sensors)
Technical importance
Improve scalability
Improve reliability
Course Overview > Distributed Systems

9. Why Study Distributed Systems?
It is very challenging
Partial failures
Network (dropped messages)
Node failures
Concurrency
Nodes execute in parallel
Messages travel asynchronously
Course Overview > Distributed Systems

10. Two Important Characteristics
No shared memory
A process does not know the current state of other processes
No global clock
Processes have different local times
Course Overview > Distributed Systems

11. No Shared Memory
A process does not know the current state of other processes
Hence messages are required
How are you?
I am fine.
Course Overview > Distributed Systems

12. No Global Clock Processes have different local times
Even within the same time zone
6:00:01.59
3:00:01.57
4:00:01.59
6:00:01.60
5:00:01.58
Course Overview > Distributed Systems

13. Theoretical Foundations
Clocks
Logical clocks (Lamport)
Partially ordered clocks (Fidge)
Causally ordered message delivery
Broadcast-based (Birman et al.)
Unicast-based (Raynal, Schiper & Toueg)
System states
Global snapshots (Chandy & Lamport)
Termination detection (Huang)
Course Overview > Distributed Systems

14. Distributed Mutual Exclusion
Permission-based (Ricart & Agrawala)
Quorum-based (Maekawa)
Token-based (Raymond)
Midterm EXAM (in class)
Course Overview > Distributed Systems

15. Synchronizing Processes
Clocks
External clock synchronization (Cristian)
Internal clock synchronization (Gusella & Zatti)
Network Time Protocol (Mills)
Decisions
Agreement protocols (Fischer)
Data
Distributed file systems (Satyanarayanan)
Memory
Distributed shared memory (Nitzberg & Lo)
Schedules
Distributed scheduling (Isard et al.)
Course Overview > Distributed Systems

16. Processes Failing & Modern Systems
Recovering from
Distributed recovery (Bernstein et al.)
Checkpoint recovery (Elonozahy et al.)
Log-based recovery (Elonozahy et al.)
Modern distributed systems
Google File System (Ghemawat et al.)
Amazon Dynamo (DeCandia et al.)
FINAL EXAM (in class)
Course Overview > Distributed Systems

17. Course Learning Objectives
Ability to understand the concepts of concurrent and distributed execution in modern operating systems and networks of systems.
Ability to understand the notion of time and clocks in a system with no global time-keeper.
Ability to understand the concept of causal ordering of events and deadlocks.
Ability to understand the concept of distributed mutual exclusion and resource management, including processor, memory, and file systems.
Ability to design new algorithms/protocols for resources management.
Ability to understand the concept of process failure and approaches to build fault-tolerance in a distributed execution environment including check pointing, voting protocols and replication.
Ability to design and conduct simulation experiments to quantitatively evaluate various distributed algorithms, and analyze and interpret the data.
Ability to communicate and work as a group on a team software project.
Course Overview

18. Syllabus Posted on the course website:
Course Overview

19. Texts No required textbook
We will use a collection of academic research papers
Posted on the course website
Expect to read one paper per lecture
Course Overview

20. Assignments 40% Exams 15% Reading Quizzes (one or two per lecture)
25% Team Project
20% In-class tests (two of them)
Course Overview > Assignments

21. Exams 40% Exams 20% Midterm Exam (in class) 20% Final Exam (in class)
Theoretical foundations
Distributed mutual exclusion
20% Final Exam (in class)
Comprehensive
Course Overview > Assignments > Exams

22. Reading Quizzes 20% Reading Quizzes ~20 quizzes
Taken at the beginning 10 minutes of each relevant lecture
Each is worth 1 point and has 5 questions (0.2 points/question)
One attempt per quiz but no forced completion
Drop the lowest 5 quiz scores
Course Overview > Assignments > Reading Quizzes

23. Team Project
In teams of 4, you will design a new distributed mutual exclusion algorithm, implement it and Maekawa’s algorithm in a testbed, and analyze multiple testbed trials to determine which algorithm is better in different scenarios.
Course Overview > Assignments > Team Project

24. Project Tasks 25% Team Project 5% Algorithm and Testbed Design
10% Testbed Implementation
10% Testbed Report
Course Overview > Assignments > Team Project

25. Team Creations Form your own teams by this weekend
Otherwise Professor Liu will assign teams and roles based on aptitudes and personal preferences
Course Overview > Assignments > Team Project

26. In-Class Tests 20% In-class tests
Course Overview > Assignments > In-Class Tests

27. Grading Scale A 90 or above A- 87-90 B+ 83-87 B 80-83 B- 77-80
F 70 or below
Course Overview > Assignments

28. Class Attendance
Required, but not graded
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29. Questions
Course Overview

30. Prerequisite Forms Course name: Advanced Operating Systems
Number: 6378
Section: 501
Prerequisites: CS 5348 Operating Systems Concepts or equivalent, and knowledge of C/C++ and UNIX
Course Overview

31. Upcoming Classes Next three lectures Logical Clocks Vector Clocks
Broadcast-based Causal Ordering
Course Overview