Skip to main content
SpringerLink
Log in

A causal consistency model based on grouping strategy

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Data consistency has always been a significant topic in distributed systems. In the existing consistency models, causal consistency attracts more attention because it can meet high-performance requirements even when there are network partitions in the system. The synchronization method between replicas is one of the key indicators affecting the performance of causal consistency, especially when there are a large number of nodes in the system. In the case of deploying a large number of nodes in the system, this paper optimizes the synchronization mode between data centers and proposes a causal consistency model based on the grouping strategy (Gart). Gart manages all nodes in groups to reduce the management cost during data synchronization, and adopt a leader mechanism to improve the management efficiency of the system. At the same time, a client migration mechanism be introduced to ensure that throughput can be improved without sacrificing the remote update visibility. The simulation results demonstrate that compared with the existing causal consistency model, Gart can achieve better throughput when handling a large number of nodes, and with the same communication delay, it can achieve higher update visibility.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Huang KL, Wei HF, Huang Y et al (2021) Byz-GentleRain: an efficient byzantine-tolerant causal consistency protocol. http://arxiv.org/abs/2109.14189 [CoRR abs]

  2. Coelho PR, Pedone F (2021) GeoPaxos+: practical geographical state machine replication. In: SRDS, pp 233–243

  3. Aldin HNS, Deldari H, Moattar MH et al (2020) Strict timed causal consistency as a hybrid consistency model in the cloud environment. Future Gener Comput Syst 105:259–274

    Article  Google Scholar 

  4. Lamport L (1978) Time, clocks, and the ordering of events in a distributed system. Commun ACM 21(7):558–565

    Article  MATH  Google Scholar 

  5. Spirovska K, Didona D, Zwaenepoel W (2021) Optimistic causal consistency for geo-replicated key-value stores. IEEE Trans Parallel Distrib Syst 32(3):527–542

    Article  Google Scholar 

  6. Tian JF, Yang QY (2021) Horae: causal consistency model based on hot data governance. J Supercomput

  7. Gunawardhana C, Bravo M, Luis ET (2017) Unobtrusive deferred update stabilization for efficient geo-replication. In: USENIX Annual Technical Conference, pp 83–95

  8. Xiang ZL, Vaidya NH (2018) Global stabilization for causally consistent partial replication. In: International Conference of Distributed Computing and Networking, pp 1–10

  9. Mohammad R, Demirbas M, Kulkarni S (2017) CausalSpartan: causal consistency for distributed data stores using hybrid logical clocks. In: Reliable distributed systems IEEE, pp 184–193

  10. Spirovska K, Didona D, Zwaenepoel W (2018) Wren: nonblocking reads in a partitioned transactional causally consistent data store. In: International Conference on Dependable Systems and Networks

  11. Huang DY, Ma XL, Zhang SL (2020) Performance analysis of the raft consensus algorithm for private blockchains. IEEE Trans Syst Man Cybern Syst 50(1):172–181

    Article  Google Scholar 

  12. Surjandari I, Yusuf H, Laoh E, Maulida R (2021) Designing a permissioned blockchain network for the Halal industry using hyperledger fabric with multiple channels and the raft consensus mechanism. J Big Data 8(1):10

    Article  Google Scholar 

  13. Peng R, Xiao H, Guo JJ et al (2020) Optimal defense of a distributed data storage system against hackers’ attacks. Reliab Eng Syst Saf 197:106790

    Article  Google Scholar 

  14. Mahmood T, Narayanan SP, Rao SG et al (2021) Karma: cost-effective geo-replicated cloud storage with dynamic enforcement of causal consistency. IEEE Trans Cloud Comput 9(1):197–211

    Article  Google Scholar 

  15. Maiya P, Kanade A (2017) Efficient computation of happens-before relation for event-driven programs. In: ISSTA, pp 102–112

  16. Xosanavongsa C, Totel E, Bettan O (2019) Discovering correlations: a formal definition of causal dependency among heterogeneous events. In: Euro S&P, pp 340–355

  17. Spirovska K, Didona D, Zwaenepoel (2019) PaRiS: causally consistent transactions with nonblocking reads and partial replication. In: International Conference on Distributed Computing Systems, pp 304–316

  18. Grusho NA, Grusho AA, Timonina EE (2020) Localizing failures with metadata. Autom Control Comput Sci 54(8):988–992

    Article  MATH  Google Scholar 

  19. Du JQ, Iorgulescu C, Roy A, Zwaenepoel W (2014) GentleRain: cheap and scalable causal consistency with physical clocks. In: Proceedings of the ACM Symposium on Cloud Computing, pp 1–13

Download references

Funding

Funding was provided by the National Natural Science Foundation of China (Grant No. 6180060654).

Author information

Authors and Affiliations

  1. Hebei University, Baoding, China

    Junfeng Tian & Yanan Pang

Authors
  1. Junfeng Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanan Pang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanan Pang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, J., Pang, Y. A causal consistency model based on grouping strategy. J Supercomput 78, 17736–17757 (2022). https://doi.org/10.1007/s11227-022-04441-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-022-04441-3

Keywords

Search

Navigation