Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data

1. Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data Akhil Kumar IEEE TRANSACTION ON COMPUTERS, VOL.40, NO.9, SEPTEMBER 1991

2. Outline • Introduction • Quorum Consensus Algorithm • Hierarchical Quorum Consensus • HQC algorithm • Availability Analysis • Tradeoffs between HQC and Related Algorithm • Conclusion

3. Introduction(1/8) • Motivations of Data Replication • Fault Tolerant • Increasing System Reliability

4. :One copy of an object Introduction(2/8) 1.Providing Fault tolerant capability in distributed system

5. The copy is using :One copy of an object Introduction(3/8) 2.Replication of data for concurrent read/write The copy is using

6. Introduction(4/8) • Two problems occur in distribution system: • RW problem • WW problem Write Read Read Write Write Write

7. 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

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

9. 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.

10. Introduction(8/8) • Our method is based on organizing the copies of an object into • extending the quorum consensus algorithm • Logical node • multilevel hierarchy

11. 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

12. 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

13. The concept of HQC

14. HQC algorithm For example: l1=3 r1+w1>3 2w1>3 2 2 1 3

15. HQC algorithm

16. HQC algorithm =

17. HQC algorithm best size worst size

18. HQC Majority Voting HQC Majority Voting Majority Voting Majority Voting HQC HQC Availability Analysis

19. HQC Majority Voting HQC Majority Voting Majority Voting Majority Voting HQC HQC Availability Analysis

20. Tradeoffs between HQC and Related Algorithm HQC is better than others fully.

21. 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