1. IS 651: Distributed Systems Midterm
Sisi Duan
Assistant Professor
Information Systems

2. HW3 Q1. Why E1->E10 and E8||E9?
Definition (->): We define e->e’ if…
Logical ordering: e->e’ if e->e’ for any process I
Messages: send (m) -> receive (m) for any message m
Transitivity: e->e’‘ if e->e’ and e’->e’’

3. HW3
Q3.B. Sequential consistency does not admit a scalable implementation because it requires a total ordering of all operations in the system. 
Q3.E. Sequential consistency is sufficient to guarantee that an airline never overbooks its seats when multiple clients reserve seats on the same airplane.

4. HW3
Q3.C. Obeying all causal orderings is sufficient to guarantee convergence of state maintained by multiple replicas. 
Q3.D. Causal consistency is sufficient to guarantee that an airline never overbooks its seats when multiple clients reserve seats on the same airplane. 
Q3.A. Sequential consistency guarantees causal ordering. 
In shared memory scenario, I think it’s true. But this is not always true.

5. Causal order vs Total order in the broadcast scenario
[Lamport, Comm. ACM 1978]
[Lamport, Distrib. Comput. 1986]
Causal order
If the broadcast of message m1 "happens before" or "causally precedes" the broadcast of message m2, then no correct process delivers m2 before it delivers m1.
m1 “Chase charges 10%!”
m2 “That is outrageous!”

6. Causal order vs Total order in the broadcast scenario✓
Causal order
Chase:
“Charge 10%”
Outrageous!
$100
$90
Chase:
“Charge 10%”
Outrageous!
$100
$90
$100

7. Causal order vs Total order in the broadcast scenario✘
Causal order
Chase:
“Charge 10%”
Outrageous!
$100
$100
$90
Chase:
“Charge 10%”
Outrageous!
$100
$90
$90
$100

8. Causal order vs Total order in the broadcast scenario✓ ✘
Causal order Total order
Chase:
“Charge 10%”
Client 1:
“Deposit $100”
Outrageous!
$100
$90
$190
Client 1:
“Deposit $100”
Chase:
“Charge 10%”
Outrageous!
$100
$200
$180
$100

9. Causal order vs Total order in the broadcast scenario✘ ✓
Causal order Total order
Chase:
“Charge 10%”
Outrageous!
$100
$100
$90
Chase:
“Charge 10%”
Outrageous!
$100
$100
$90
$100

10. Causal order vs Total order in the broadcast scenario✓ ✓
Causal order Total order
Chase:
“Charge 10%”
Client 1:
“Deposit $100”
Outrageous!
$100
$90
$190
Chase:
“Charge 10%”
Client 1:
“Deposit $100”
Outrageous!
$100
$90
$190
$100

11. Midterm 25% of the score Oct 17, in-class, 2.5 hours
Covers slides 1(intro)-6(consistency)
Closed-book
One A4 page cheat sheet (front and back) – You prepare it.
Turn in the cheat sheet (with your name) at the end of the exam

12. Midterm Multiple choices Short answers/diagrams
Similar with class exercises
Short answers/diagrams
Similar with homework
No programming questions. But I may ask concepts.
Advice
Explanation can help you get partial credit even your answer is not correct.
Be brief, but not too simple.

13. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

14. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

15. Distributed Systems Overview
What is a distributed system?
Who? What? How?
What are the architecture and design philosophy?
Scalability
Reliability
Performance
Openness

16. Distributed Systems Overview
Distributed systems goals
Raise the level of abstraction, provide location transparency, scalability, availability, modularity
Distributed systems challenges
Interfaces, scalability, consistency, fault tolerance, security

17. Distributed Systems Overview
Network layers
P2P
Onion Routing

18. Distributed Systems Overview

19. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

20. Web Technology
Client-Server Model

21. Web Technology: 3-tier architecture
What is good/bad about this architecture?
+ Modularity, better reliability/scalability
- poor latency

22. Web Technology Real Architecture Why so many layers? De-coupling
Performance
Scalability
Security …

23. Web Service Usually more complicated Coordination is challenging
Services from multiple providers
Coordination is challenging

24. Web Service Load balancing Content-aware distribution
Always distribute the same request for the same document to the same server

25. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

26. Distributed Communication
Sockets
Remote Procedure Call
Distributed Shared Memory

27. Distributed Communication
TCP vs UDP

28. sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.bind((hostname, port))
sock.listen(1)
conn,addr = sock.accept()
server_addr=(hostname,portnum)
sock.connect(server_addr)
sock.sendall(msg)
buf = conn.recv(8092)
sock.close()

29. Distributed Communication
Socket
interface

30. Distributed Communication
Remote Procedure Call (RPC)

31. Distributed Communication
RPC
XML/RPC
SOAP
RPC-style
Document-style
Both use XML
Advantages?
Disadvantages?

32. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

33. Time and Synchronization
Why?
Synchronizing real clocks
Cristian’s algorithm
The Berkeley Algorithm
Network Time Protocol (NTP)
Logical clocks
Lamport logical clocks
Vector clocks

34. Time and Synchronization
Synchronizing real clocks
Christian’s algorithm
Berkerley algorithm
NTP
Never perfect

35. Time and Synchronization
Lamport clock
L(e1) = 1 (pitcher throws ball to home)
L(e2) = 2 (ball arrives at home)
L(e3) = 3 (batter hits ball to pitcher)
L(e4) = 4 (batter runs to first base)
L(e5) = 1 (runner runs to home)
L(e6) = 4 (ball arrives at pitcher)
L(e7) = 5 (pitcher throws ball to first base)
L(e8) = 5 (runner arrives at home)
L(e9) = 6 (ball arrives at first base)
L(e10) = 7 (batter arrives at first base)

36. Time and Synchronization
Vector Clock

37. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

38. Mutual Exclusion What’s mutual exclusion? Why? Goals? While true:
Perform local operations
Acquire()
Execute critical section
Release()

39. Mutual Exclusion Centralized Solution Ring based Solution
While true:
Perform local operations
Acquire()
Execute critical section
Release()
Mutual Exclusion
Centralized Solution
Ring based Solution
Shared priority queue
Majority voting

40. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

41. GFS Architecture Client retrieves metadata from master
Read/Write data flows between client and chunkserver
Minimizing the master’s involvement in read/write operations alleviates the single-master bottleneck

42. Distributed File Systems

43. What we have discussed so far
Distributed systems overview
Web technologies
Distributed communication
Time and synchronization
Mutual exclusion
Distributed File systems
Consistency

44. Consistency Shared memory Consistency model Rules
”contract” between memory system and programmer

46. Consistency Models Strict consistency Sequential consistency
Causal consistency
Eventual consistency