practical byzantine fault tolerance and proactive recovery

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Practical Byzantine Fault Tolerance and Proactive Recovery

Miguel Castro and Barbara LiskovACM TOCS ‘02

Presented By: Imranul Hoque

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Problem

• Computer systems provide crucial services• Computer systems fail– Natural disasters– Hardware failures– Software errors– Malicious attacks

• Need highly available service

Replicate to increase availability

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Assumptions are a ProblemBefore BFT BFT

Behavior of faulty process

Fail stop failure[Paxos, VS Replication]

Byzantine failure

Synchrony Synchronous system[Rampart, SecureRing]

Asynchronous system!• Safety without synchrony• Liveness with eventual time bound

Number of faults

Bounded Unbounded if less then one third fail in a time period• Proactive and frequent recovery[When will this not work?]

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Contributions

• Practical replication algorithm– Weak assumption– Good performance [Really?]

• Implementation– BFT: A generic replication toolkit– BFS: A replicated file system

• Performance evaluation

Byzantine Fault Tolerance in Asynchronous Environment

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Challenges

Request A Request B

Client Client

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Challenges

2: Request B

1: Request A

Client Client

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State Machine Replication

2: Request B

1: Request A

2: Request B

1: Request A

2: Request B

1: Request A

2: Request B

1: Request A

Client Client

How to assign sequence number to requests?

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Primary Backup Mechanism

Client Client

2: Request B

1: Request A

What if the primary is faulty?Agreeing on sequence number

Agreeing on changing the primary (view change)

View 0

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Agreement

• Certificate: set of messages from a quorum• Algorithm steps are justified by certificates

Quorum BQuorum A

Quorums have at least 2f + 1 replicas

Quorums intersect in at least one correct replica

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Algorithm Components

• Normal case operation• View changes• Garbage collection• Recovery

All have to be designed to work together

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Normal Case Operation

• Three phase algorithm:– PRE-PREPARE picks order of requests– PREPARE ensures order within views– COMMIT ensures order across views

• Replicas remember messages in log• Messages are authenticated– {.}σk denotes a message sent by k

Quadratic message exchange

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Pre-prepare Phase

Primary: Replica 0

Replica 1

Replica 2

Replica 3

Request: m

{PRE-PREPARE, v, n, m}σ0

Fail

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Prepare PhaseRequest: m

PRE-PREPARE

Primary: Replica 0

Replica 1

Replica 2

Replica 3 Fail

Accepted PRE-PREPARE

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Prepare PhaseRequest: m

PRE-PREPARE

Primary: Replica 0

Replica 1

Replica 2

Replica 3 Fail

{PREPARE, v, n, D(m), 1}σ1

Accepted PRE-PREPARE

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Prepare PhaseRequest: m

PRE-PREPARE

Primary: Replica 0

Replica 1

Replica 2

Replica 3 Fail

{PREPARE, v, n, D(m), 1}σ1

Accepted PRE-PREPARE

Collect PRE-PREPARE + 2f matching PREPARE

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Commit PhaseRequest: m

PRE-PREPARE

Primary: Replica 0

Replica 1

Replica 2

Replica 3 Fail

PREPARE

{COMMIT, v, n, D(m)}σ2

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Commit Phase (2)Request: m

PRE-PREPARE

Primary: Replica 0

Replica 1

Replica 2

Replica 3 Fail

PREPARE COMMIT

Collect 2f+1 matching COMMIT: execute and reply

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View Change

• Provide liveness when primary fails– Timeouts trigger view changes– Select new primary (= view number mod 3f+1)

• Brief protocol– Replicas send VIEW-CHANGE message along with

the requests they prepared so far– New primary collects 2f+1 VIEW-CHANGE messages– Constructs information about committed requests

in previous views

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View Change Safety

• Goal: No two different committed request with same sequence number across views

Quorum for Committed Certificate (m, v, n)

At least one correct replica has Prepared Certificate (m, v, n)

View Change Quorum

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Recovery

• Corrective measure for faulty replicas– Proactive and frequent recovery– All replicas can fail if at most f fail in a window

• System administrator performs recovery, or• Automatic recovery from network attacks– Secure co-processor– Read-only memory– Watchdog timer

Clients will not get reply if more than f replicas are recovering

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Sketch of Recovery Protocol

• Save state• Reboot with correct code and restore state– Replica has correct code without losing state

• Change keys for incoming messages– Prevent attacker from impersonating others

• Send recovery request r– Others change incoming keys when r execute

• Check state and fetch out-of-date or corrupt items– Replica has correct up-to-date state

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Performance

• Andrew benchmark– Andrew100 and Andrew500

• 4 machines: 600 MHz, Pentium III• 3 Systems– BFS: based on BFT– NO-REP: BFS without replication– NFS: NFS-V2 implementation in Linux

No experiment with faulty replicasScalability issue: only 4 & 7 replicas

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Benchmark Results (w/o PR)

Without view change and faulty replica!

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Benchmark Results (with PR)Recovery Period

Recovery is staggered!

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Related WorksFault Tolerance

Fail Stop Fault TolerancePaxos

1989 (TR)

VS ReplicationPODC 1988

Byzantine Fault ToleranceByzantine

Agreement

Rampart

TPDS 1995SecureRingHICSS 1998BFT TOCS ‘02

BASETOCS ‘03

Byzantine

Quorums

Malkhi-

ReiterJDC

1998Phalanx

SRDS 1998FleetToKDI

‘00Q/USOSP ‘05

Hybrid Quorum

HQ Replication OSDI ‘06

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Today’s Talk

Replication in Wide Area NetworkProf. Keith Marzullo

Distinguished Lectureship SeriesToday @ 4PM – 1404 SC

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Questions?

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Backup Slides

• Optimization• Proof of 3f+1 optimality• Garbage Collection• View Change with MAC• Detailed Recovery Protocol• State Transfer

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Optimization

• Using MAC instead of Digital Signatures• Replying with digest• Tentative execution of Read-Write requests• Tentative execution or Read-only requests• Piggyback COMMIT with next PRE-PREPARE• Request batching

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Proof of 3f+1 Optimality

• f faulty replicas• Should reply after n-f replicas respond to ensure

liveness• Two n-f quorums intersect in at least n-2f replicas• Worst case scenario: out of (n-2f), f are faulty• Two quorums should have at least 1 non-faulty

replica in common– Therefore, n-3f >= 1

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Garbage Collection

• Replicas should remove from their logs information about executed operations.– Even if i has executed a request, it may not be safe

to remove that request's information because of a subsequent view change.

– Use periodic checkpointing (after K requests).

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Garbage Collection• When replica i produces a checkpoint it multicasts

{CHECKPOINT, n, d, i}αi.– n is the highest sequence number of the requests i has

executed.– d is a digest of the current state.

• Each replica collects such messages until it has a quorum certificate with 2f + 1 authenticated CHECKPOINT messages with the same n and d from distinct i.– Called the stable certificate: all other replicas will be able to

obtain a weak certificate proving that its stable checkpoint is correct if they need to fetch it.

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Garbage Collection

• Once a replica has a stable certificate for a checkpoint with sequence number n, then that checkpoint is stable.– The replica can discard all entries in the log with

sequence numbers less than n and all checkpointed states ealier than n.

• The checkpoint can be used to define high and low water marks for sequence numbers:– L = n– H = n + LOG for a log size LOG.

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View Change with MAC

• Replica has logged per message m:– m = {REQUEST, o, t, c} αc

– {PRE-PREPARE, v, n, D(m)} αp

• m is pre-prepared at this replica

– {PREPARE, v, n, D(m), i} αi from 2f replicas• m is prepared at this replica

– {COMMIT, v, n, i}αi from 2f+1 replicas• m is commited at this replica

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View Change with MAC

• At a high level:– The primary of view v + 1 reads information about

stable and prepared certificates from a quorum– It then computes the stable checkpoint and fills in

the command sequence– It sends this information to the backups.– The backups verify this information.

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View Change with MAC

• Each replica i maintains two sets P and Q:– P contains tuples {n, d, v} such that i has collected

a prepared certificate for request with digest d for view v, sequence n and there is no such request with sequence n for a later view.

– Q contains tuples {n, d, v} such that i pre-prepared request for request with digest d for view v, sequence n and there is no such request with sequence n for a later view.

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View Change with MAC

• When i suspects the primary for view v has failed:– Enter view v + 1– Multicast {VIEW-CHANGE, v+1, h, C, P, Q, i}αi

– h is the sequence number of the stable checkpoint of i.

– C is a set of checkpoints at i with their sequence number.

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View Change with MAC

• Replicas collect VIEW-CHANGE messages and acknowledge them to primary p of view v + 1.– Accepts a message only if the values in their P and

Q are earlier than the new view number.– {VIEW-CHANGE-ACK, v+1, i, j, d}μi

– i is sender of ack.– j is source of the VIEW-CHANGE message.– d is the digest of the VIEW-CHANGE message

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View Change with MAC

• The primary p:– Stores VIEW-CHANGE from i in S[i] if gets 2f − 1

corresponding VIEW-CHANGE-ACKs.– Call a view-change certificate– Chooses from S a checkpoint and sets of requests.– Try to do whenever update S.

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View Change with MAC

• Select checkpoint for starting state for processing requests in the new view.– Picks checkpoint with the highest number h from

the set of checkpoints that are known to be correct (at least f + 1 of them) and that have numbers higher than the low water mark of at least f +1 non-faulty replicas (so ordering information is available).

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View Change with MAC

• Select a request to pre-prepare in the new view for each n between h and h + Log.– If m committed in an earlier view, then choose m.– If there is a quorum of replicas that did not

prepare any request for n, then p pre-proposes a null command.

• Multicast decision to backups.– Each can verify by running the same decision

procedure.

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Recovery Protocol

• Save state• Reboot with correct code and restore state– Replica has correct code without losing state

• Change keys for incoming messages– Prevent attacker from impersonating others

• Estimate high-water mark in a correct log (H)– Bound sequence number of bad information by H

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Recovery Protocol

• Send recovery request r– Others change incoming keys when r executes– Bound sequence number of forged messages by Hr

(high water mark in log when r executes)• Participate in algorithm– May be needed to complete recovery if not faulty

• Check state and fetch out-of-date or corrupt items• End: checkpoint max(H, Hr) is stable– Replica has correct up-to-date state

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State Transfer