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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

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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


The concept of hqc1

The concept of HQC


Hqc algorithm

HQC algorithm

For example:

l1=3

r1+w1>3

2w1>3

2 2

1 3


Hqc algorithm1

HQC algorithm


Hqc algorithm2

HQC algorithm

=


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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