1. EEC 688/788 Secure and Dependable Computing
Lecture 11
Wenbing Zhao
Department of Electrical and Computer Engineering
Cleveland State University

2. EEC688/788: Secure & Dependable Computing
Outline
Distributed consensus and Paxos algorithms
Distributed consensus problem
Classic Paxos
Multi-Paxos
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EEC688/788: Secure & Dependable Computing

3. Distributed Consensus
Distributed consensus is a fundamental problem in distributed computing
Ensure replica consistency
Asynchronous distributed system
No upper bound on processing time
No upper bound on clock drift rate
No upper bound on networking delay
In an asynchronous distributed system, you cannot tell a crashed process from a slow one, even if you can assume that messages are sequenced and retransmitted (arbitrary numbers of times), so they eventually get through
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EEC688/788: Secure & Dependable Computing

4. FLP Impossibility Results
FLP (Fischer, Lynch and Paterson) Impossibility result
A single faulty process can prevent consensus
Because a slow process is indistinguishable from a crashed one
Chandra/Toueg Showed that FLP Impossibility applies to many problems, not just consensus
In particular, they show that FLP applies to group membership, reliable multicast
So these practical problems are impossible to solve in asynchronous systems
They also look at the weakest condition under which consensus can be solved
Ways to bypass the impossibility result
Use unreliable failure detector
Use a randomized consensus algorithm
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EEC688/788: Secure & Dependable Computing

5. Distributed Consensus
Older generation of consensus algorithms rely on the use of an unreliable failure detector to exclude failed processes from the consensus consideration
Difficult to understand and harder to prove for correctness
The Paxos algorithm introduced by Lamport
Separate safety and liveness properties
“Paxos is among the simplest and most obvious of distributed algorithm” by Lamport
Consensus can be reached during periods of synchrony
No consensus is possible if system very asynchronous, but guarantees no disagreement
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EEC688/788: Secure & Dependable Computing

6. EEC688/788: Secure & Dependable Computing
Consensus Problem
Safety:
Only a value that has been proposed may be chosen
If a value is chosen by a process, then the same value must be chosen by any other process that has chosen a value
If a process learns a value, then the value must have been chosen by some process
Liveness:
Some proposed value is eventually chosen and, if a value has been chosen, then a process can eventually learn the value
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EEC688/788: Secure & Dependable Computing

7. The Paxos Algorithm – Consensus for Asynchronous Distributed Systems
Contribution: separately consider safety and liveness issues. Safety can be guaranteed and liveness is ensured during period of synchrony
Participants of the algorithm are divided into three categories
Proposers: those who propose values
Accepters: those who decide which value to choose
Learners: those who are interested in learning the value chosen
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EEC688/788: Secure & Dependable Computing

8. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
How to choose a value
Use a single acceptor: straightforward but not fault tolerant
Use a number of acceptors: a value is chosen if the majority of the acceptors have accepted it
Accepted does not mean chosen. However, if a value has been chosen, it must have been accepted first
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EEC688/788: Secure & Dependable Computing

9. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
Requirements for choosing a value
P1. An acceptor must accept the first proposal that it receives
P2. If a proposal with value v is chosen, then every higher-numbered proposal that is chosen has value v
Since the proposal numbers are totally ordered, P2 guarantees the safety property
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EEC688/788: Secure & Dependable Computing

10. The Paxos Algorithm How to guarantee P2?
P2a: If a proposal with value v is chosen, then every higher-numbered proposal accepted by any acceptor has value v
But what if an acceptor that has never accepted v accepted a proposal with v’?
P2b: if a proposal with value v is chosen, then every higher-numbered proposal issued by any proposer has value v
P2b implies P2a, which implies P2
P2b
P2a P2
V is chosen
by some acceptor
Newer proposal
Must propose v
Only v could
Have been accepted
Only v could
Have been chosen by other acceptors
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EEC688/788: Secure & Dependable Computing

11. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
How to ensure P2b?
P2c: For any v and n, if a proposal with value v and number n is issued, then there is a set S consisting of a majority of acceptors such that either
(a) no acceptor in S has accepted any proposal numbered less than n, or
(b) v is the value of the highest-numbered proposal among all proposals numbered less than n accepted by the acceptors in S
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EEC688/788: Secure & Dependable Computing

12. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
To ensure P2c, an acceptor must promise:
It will not accept any more proposals numbered less than n, once it has accepted a proposal n
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EEC688/788: Secure & Dependable Computing

13. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
Phase 1.
(a) A proposer selects a proposal number n and sends a prepare request with number n to a majority of acceptors.
(b) If an acceptor receives a prepare request with number n greater than that of any prepare request to which it has already responded, then it responds to the request with a promise not to accept any more proposals numbered less than n and with the highest-numbered proposal (if any) that it has accepted.
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EEC688/788: Secure & Dependable Computing

14. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
Phase 2.
(a) If the proposer receives a response to its prepare requests (numbered n) from a majority of acceptors, then it sends an accept request to each of those acceptors for a proposal numbered n with a value v, where v is the value of the highest-numbered proposal among the responses, or is any value if the responses reported no proposals.
(b) If an acceptor receives an accept request for a proposal numbered n, it accepts the proposal unless it has already responded to a prepare request having a number greater than n.
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EEC688/788: Secure & Dependable Computing

15. EEC688/788: Secure & Dependable Computing
The Paxos Algorithm
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EEC688/788: Secure & Dependable Computing

16. Importance of Keeping Promises (for not accepting older proposal)
Not a problem if a value has been chosen
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EEC688/788: Secure & Dependable Computing

17. Importance of Keeping Promises (for not accepting older proposal)
Safety violated without promise with competing proposers
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EEC688/788: Secure & Dependable Computing

18. Importance of Keeping Promises (for not accepting older proposal)
Safety is ensured by the promise with competing proposers
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EEC688/788: Secure & Dependable Computing

19. Multi-Paxos: Paxos for State Machine Replication
Client: partially assumes the role of a proposer
Server replicas: acceptors
Value to be agreed on: total ordering of requests sent by clients
Total ordering accomplished by running a sequence of instances of Paxos
Each instance is assigned a sequence number, representing the total ordering of the request that is chosen
Value to be chosen: the request chosen for the instance

20. Multi-Paxos: Paxos for State Machine Replication
Client: partially assumes the role of a proposer
Only propose a value (i.e., request it sends) without the corresponding proposal number
A server replica, the primary, decides on the proposal number
Primary: essentially the proposer in Paxos
Propose a sequence number – request binding
Propagate value chosen (i.e., total ordering info) to other replicas (i.e., learners)
Initial membership is known with a sole primary
First phase can be omitted during normal operation
When the primary is suspected, a new primary is elected (view change)

21. Multi-Paxos: Paxos for State Machine Replication
Normal operation of Multi-Paxos

22. Multi-Paxos: Checkpointing and Garbage Collection
Paxos is open-ended: it never terminates
A proposer is allowed to initiate a new proposal even if every acceptor has accepted a proposal
An acceptor must remember the last proposal that it has accepted and the latest proposal number it has accepted
In Multi-Paxos, every replica must remember such info for every instance of Paxos: Need infinite memory
Solution: periodic checkpointing, e.g., once for every n requests
Garbage collect logs after taking each checkpoint
Request or control msg needed by a slow replica may not be available anymore after a checkpoint => state transfer

23. Multi-Paxos: Leader Election and View Change
Leader election: can be done using a full Paxos instance
New primary needs to determine if a value has been chosen in each incomplete instance of Paxos
Leader election and history determination can be done in a simple full paxos: view change

24. Multi-Paxos: View Change
A set of 2f+1 replicas, replica id: 0,1,…,2f
History of system: a sequence of views
Each view: one and only one primary
Initially replica 0 assumes the primary role for v=0
Subsequently, replicas take the primary role in a round-robin fashion
To ensure liveness
A replica starts a view change timer on the initiation of each instance of Paxos
If the replica does not learn the request chosen before timer expires => suspect the primary

25. View Change
On suspecting the primary, a replica broadcasts a view change message to all
Current primary, if it is wrongly suspected, joins the view change anyway (i.e., it steps down from primary role)
A replica joins the view change even if it’s view change timer has not expired yet
On joining view change, a replica stops accepting normal control msgs and respond to only checkpointing and view change msgs

26. View change View change msg contains
New view #
Seq# of last stable checkpoint
A set of accepted records since last stable checkpoint
Each record consists of view#, seq#, request msg
On receiving f+1 view change msgs, new primary sends new view msg
Include a set of accept msgs
Include all accepted msgs as part of view change msg
When a gap in seq# is detected, create an accept request with no op
A replica accepts new view msg if it has not installed a newer view

27. Exercise 1:
There are 2 proposers p1 and p2, 3 acceptors a1, a2, a3. Proposer p1 sends a prepare request to a1 and a2 with (p#=1). Proposer p2 sends a prepare request to a2 and a3 with (p#=2). a1 and a2 reply to proposer p1 that they received the proposal p1(p#=1). Similarly a2 and a3 reply to proposer p2 that they received the proposal p2(p#=2).
If p1 then sends an accept request to a1 and a2 with (p#=1, v#=2), what happens at a1 and a2?
If proposer p2 sends a accept request to a2 and a3 with (p#=2, v3#=3), what happens at a2 and a3?
If proposer 1 again sends a new proposal and accept request, say p3, to a1 and a2 with (p#=3), does a1 and a2 accept the proposal? Assume that the value is already chosen in question b, what is the final value chosen for this new proposal?