hierarchical quorum consensus: a new algorithm for managing replicated data akhil kumar ieee...
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Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data
Akhil KumarIEEE TRANSACTION ON COMPUTERS, VO
L.40, NO.9, SEPTEMBER 1991
Outline
• Introduction• Quorum Consensus Algorithm• Hierarchical Quorum Consensus• HQC algorithm• Availability Analysis• Tradeoffs between HQC and Related
Algorithm• Conclusion
Introduction(1/8)
• Motivations of Data Replication1. Fault Tolerant
2. Increasing System Reliability
Introduction(2/8)1.Providing Fault tolerant capability in distributed system
:One copy of an object
Introduction(3/8)2.Replication of data for concurrent read/write
The copy is using
:One copy of an object
The copy is using
Introduction(4/8)
• Two problems occur in distribution system:– RW problem
– WW problem
Read
Write
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.
Read quorum
Write quorum
Introduction(6/8)
• The solution : intersect property of read/write quorum– RW problem
– WW problem
Read and WriteRead quorum Write quorum
Write and Writewrite quorum Write quorum
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)
• 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 WriteRead quorum Write quorum
The quorum intersection conditions:
Read and WriteRead quorum Write quorum
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
best size
The concept of HQC
HQC algorithm
For example:l1=3
r1+w1>3
2w1>3
2 2
1 3
HQC algorithm
HQC algorithm
=
HQC algorithm
best size
worst size
Availability Analysis
HQC
Majority Voting
HQC Majority Voting
HQC
Majority Voting
HQC Majority Voting
Availability Analysis
HQC
Majority Voting
HQC Majority Voting
HQC
Majority Voting
HQC Majority Voting
Tradeoffs between HQC and Related Algorithm
HQC is better than others fully.
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