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Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data . Akhil Kumar IEEE TRANSACTION ON COMPUTERS, VOL.40, NO.9, SEPTEMBER 1991. Outline. Introduction Quorum Consensus Algorithm Hierarchical Quorum Consensus HQC algorithm Availability Analysis

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hierarchical quorum consensus a new algorithm for managing replicated data

Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data

Akhil Kumar

IEEE TRANSACTION ON COMPUTERS, VOL.40, NO.9, SEPTEMBER 1991

outline
Outline
  • Introduction
  • Quorum Consensus Algorithm
  • Hierarchical Quorum Consensus
  • HQC algorithm
  • Availability Analysis
  • Tradeoffs between HQC and Related Algorithm
  • Conclusion
introduction 1 8
Introduction(1/8)
  • Motivations of Data Replication
    • Fault Tolerant
    • Increasing System Reliability
introduction 2 8

:One copy of an object

Introduction(2/8)

1.Providing Fault tolerant capability in distributed system

introduction 3 8

The copy is using

:One copy of an object

Introduction(3/8)

2.Replication of data for concurrent read/write

The copy is using

introduction 4 8
Introduction(4/8)
  • Two problems occur in distribution system:
    • RW problem
    • WW problem

Write

Read

Read

Write

Write

Write

introduction 5 8
Two operations of quorum structure in distribution system:

Read operation

To access all of the copies in a read quorum

a copy with the highest version number is returned

Write operation

To write to all of the copies in a write quorum

assigns each copy the version number that is one more than the maximum version number encountered in the write quorum.

Introduction(5/8)

Read quorum

Write quorum

introduction 6 8

Read and Write

Write and Write

Read quorum

write quorum

Write quorum

Write quorum

Introduction(6/8)
  • The solution : intersect property of read/write quorum
    • RW problem
    • WW problem
introduction 7 8
Introduction(7/8)
  • This paper generalizes the quorum consensus scheme (QC)
    • into a multilevel algorithm called hierarchical quorum consensus (HQC)
    • shows that given a collection of n copies of an object, the minimum size of a quorum is n0.63 copies.
  • A smaller quorum size results in a lower cost of synchronization.
introduction 8 8
Introduction(8/8)
  • Our method is based on organizing the copies of an object into
    • extending the quorum consensus algorithm
    • Logical node
    • multilevel hierarchy
qc algorithm
8 copies let n=8+1

qr+qw > 9

2qw > 9

5 5

4 6

. .

. .

9 copies let n=9+1

qr+qw > =10

2qw > =10

5 5

4 6

. .

. .

Read and Write

Read quorum

Write quorum

The quorum intersection conditions:

Read and Write

Read quorum

Write quorum

QC Algorithm
the concept of hqc

best size

The concept of HQC
  • An example of 2-level

l1=3 l2=3

r1+w1>3 r2+w2>3

2w1>3 2w2>3

2 2 2 2 4 4

1 3 1 3 1 9

1 3 2 2 2 6

r w

hqc algorithm
HQC algorithm

For example:

l1=3

r1+w1>3

2w1>3

2 2

1 3

hqc algorithm3
HQC algorithm

best size

worst size

availability analysis

HQC Majority Voting

HQC Majority Voting

Majority Voting

Majority Voting

HQC

HQC

Availability Analysis
availability analysis1

HQC Majority Voting

HQC Majority Voting

Majority Voting

Majority Voting

HQC

HQC

Availability Analysis
tradeoffs between hqc and related algorithm
Tradeoffs between HQC and Related Algorithm

HQC is better than others fully.

conclusion
Conclusion
  • In this paper, they introduced a new algorithm, also based on voting, and showed that:
    • It is possible to reduce the size of a quorum from (n+1)/2copies (as in majority voting) to n0.63 copies
    • The HQC method produces certain intersecting sets of quorums that cannot be produced in a single-level vote assignment
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