Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

A randomized algorithm for the wait-free consensus problem

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

Abstract

A wait-free consensus technique is provided with endless processes utilizing a shared memory model. When a powerful adversary is allowed to view and destroy infinite number of votes, the approach weighted voting can be used to reach consensus with at least constant probability. In asynchronous system, there is no known upper bound to transmit the message from source to destination processor. This paper presents a resilient and message-efficient algorithm by aggregating the votes of individual processors to solve the wait-free consensus in asynchronous systems. We considered an adaptive adversary and message-passing communication system. Our aim is to construct a message-passing algorithm equivalent to a weak shared coin and to provide a message-efficient algorithm for aggregating the votes of individual processors. A processor announces votes to smaller groups before propagating them to larger ones. To limit generated, received, or sent, vote weights are gradually increased. The wait-free consensus problem is optimally solved by our algorithm, which demonstrates an effective message-passing execution of the shared coin. When less than n/2 processes are faulty or crashed, the predicted message complexity of this randomized consensus procedure is O (n2 (log log n)2). This is a linear improvement over the previous best protocol and is close to a message lower bound.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability statement

My manuscript has no associated data.

References

  1. Baliga A (2017) Understanding Blockchain Consensus Models [White Paper]. Semanticscholar.org, 4:1–14, [Online]. Available: https://www.persistent.com/wp-content/uploads/2017/04/WP-Understanding-Blockchain-Consensus-Models.pdf

  2. Nawab F, Sadoghi M (2019) Blockplane: a global-scale byzantizing middleware. In: Proc Int Conf Data Eng, pp 124–135. Doi: https://doi.org/10.1109/ICDE.2019.00020

  3. Fischer MJ, Lynch NA, Paterson MS (1985) Impossibility of distributed consensus with one faulty process. J Assccktion Comput Mach 32(2):374–382

    Article  MATH  Google Scholar 

  4. Loui M, Abu-Amara H (1987) Memory requirements for agreement among unreliable asynchronous processes. Adv Comput Res 4:163–183

    Google Scholar 

  5. Srinivasan S, Kandukuri R (2022) Solving consensus in true partial synchrony. IEEE Trans Parallel Distrib Syst 33(12):3478–3490. https://doi.org/10.1109/TPDS.2022.3156925

    Article  Google Scholar 

  6. Aguilera MK, Toueg S (2012) The correctness proof of Ben-Or’s randomized consensus algorithm. Distrib Comput 25(5):371–381. https://doi.org/10.1007/s00446-012-0162-z

    Article  MATH  Google Scholar 

  7. Aspnes J (1998) Lower bounds for distributed coin-flipping and randomized consensus.pdf. J ACM 45(3):415–450

    Article  MATH  Google Scholar 

  8. Pease M, Shostak R, Lamport L (1980) Reaching agreement in the presence of faults. J ACM 27(2):228–234. https://doi.org/10.1145/322186.322188

    Article  MATH  Google Scholar 

  9. Pirnazar M et al (2018) The evaluation of the usage of the fuzzy algorithms in increasing the accuracy of the extracted land use maps. Int J Glob Environ Issues 17(4):307–321. https://doi.org/10.1504/IJGENVI.2018.095063

    Article  Google Scholar 

  10. Trivedi SA, Pattanaik KK (2020) A sensor-actor coordination protocol for variable rate irrigation. In: 14th IEEE Int Conf Appl Inf Commun Technol AICT 2020—Proc, pp 1–6, Doi: https://doi.org/10.1109/AICT50176.2020.9368742

  11. Aspnes J (2003) Randomized protocols for asynchronous consensus. Distrib Comput 16(2–3):165–175. https://doi.org/10.1007/s00446-002-0081-5

    Article  MATH  Google Scholar 

  12. Aspnes J, Attiya H, Censor K (2008) Randomized consensus in expected O(n log n) individual work. Proc Annu ACM Symp Princ Distrib Comput, pp 325–333. Doi: https://doi.org/10.1145/1400751.1400794

  13. Aspnes J, Attiya H, Censor K (2012) Polylogarithmic concurrent data structures from monotone circuits. J ACM 59(1), 24

  14. Aspnes J, Herlihy M (1990) Fast randomized shared consensus memory * using. J Alg, vol 461

  15. Aspnes J , Waarts O (1996) Randomized consensus in expected o(nlog2n) operations per processor* 25(5):1024–1044

  16. Attiya H (2008) Tight bounds for asynchronous randomized consensus.pdf 55(5):26

  17. Bracha G, Rachman O (1992) Randomized consensus in expected O(n2 log n) operations. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinf), vol 579 LNCS, pp 143–150. Doi: https://doi.org/10.1007/BFb0022443

  18. Fich F, Herlihy M, Shavit N (1998) On the space complexity of randomized synchronization. J ACM 45(5):843–862. https://doi.org/10.1145/290179.290183

    Article  MATH  Google Scholar 

  19. Alistarh D, Aspnes J, King V, Saia J (2018) Communication-efficient randomized consensus. Distrib Comput 31(6):489–501. https://doi.org/10.1007/s00446-017-0315-1

    Article  MATH  Google Scholar 

  20. Chandra TD (1996) Polylog randomized wait-free consensus. Proc Annu ACM Symp Princ Distrib Comput, pp 166–175. Doi: https://doi.org/10.1145/248052.248083

  21. Attiya H, Bar-Noy A, Dolev D (1995) Sharing memory robustly in message-passing systems. J ACM 42(1):124–142. https://doi.org/10.1145/200836.200869

    Article  MATH  Google Scholar 

  22. Wang H, Lin B (2007) Pipelined van emde boas tree: algorithms, analysis, and applications. Proc IEEE INFOCOM, pp2471–2475. Doi: https://doi.org/10.1109/INFCOM.2007.303

  23. Aspnes J, Censor K (2010) Approximate shared-memory counting despite a strong adversary. ACM Trans Algo 6(2):25

  24. Chor B, Israeli A, Li M (1987) On processor coordination using asynchronous hardware. Proc Annu ACM Symp Princ Distrib Comput, vol Part F1302, pp 86–97. Doi: https://doi.org/10.1145/41840.41848

  25. Abrahamson K (1988) On achieving consensus using a shared memory. Proc Annu ACM Symp Princ Distrib Comput, vol Part F1301, pp 291–302. Doi: https://doi.org/10.1145/62546.62593

  26. Saks M, Shavit N, Woll H (1991) Optimal time randomized consensus—Making resilient algorithms fast in practice. Proc Annu ACM-SIAM Symp Discret Algo, pp 351–362

  27. Lundstrom O, Raynal M, Schiller EM (2021) Self-stabilizing multivalued consensus in asynchronous crash-prone systems. Proc 2021 17th Eur Dependable Comput Conf EDCC, pp 111–118. Doi: https://doi.org/10.1109/EDCC53658.2021.00023

  28. Alistarh D, Ellen F, Rybicki J (2021) Wait-free approximate agreement on graphs. Lect Notes Comput Sci, 12810

  29. Guerraoui R, Kuznetsov P, Monti M, Pavlovic M, Seredinschi DA (2022) The consensus number of a cryptocurrency. Distrib Comput 35(1):1–15. https://doi.org/10.1007/s00446-021-00399-2

    Article  MATH  Google Scholar 

  30. Lamport L, Shostak R, Pease M (1982) The byzantine generals problem. ACM Trans 4(3):382–401

    MATH  Google Scholar 

  31. Raynal M, Taubenfeld G (2021) Fully anonymous consensus and set greement algorithms. Netw Syst. pp 314–328

  32. Herlihy M (1991) Wait-free synchronization. ACM Trans Program Lang Syst 13(1):124–149. https://doi.org/10.1145/114005.102808

    Article  Google Scholar 

  33. Perrin M, Mostéfaoui A, Bonin G, Courtillat-Piazza L (2022) Extending the wait-free hierarchy to multi-threaded systems. Distrib Comput. https://doi.org/10.1007/s00446-022-00425-x

    Article  MATH  Google Scholar 

  34. Heydari H, Silvestre G, Arantes L (2021) Efficient consensus-free weight reassignment for atomic storage. 2021 IEEE 20th Int Symp Netw Comput Appl NCA 2021. Doi: https://doi.org/10.1109/NCA53618.2021.9685401.

  35. Chlebus BS, Kowalski DR (2006) Time and communication efficient consensus for crash failures. Distrib Comput, vol 4167

  36. Chlebus BS, Kowalski DR (2006) Robust gossiping with an application to consensus. J Comput Syst Sci 72(8):1262–1281. https://doi.org/10.1016/j.jcss.2006.08.001

    Article  MATH  Google Scholar 

  37. Chlebus BS, Kowalski DR (2009) Fast scalable deterministic consensus for crash failures categories and subject descriptors. Science(80):111–120

  38. Biswas A, Tripathi AK, Aknine S (2021) Lea-TN: leader election algorithm considering node and link failures in a torus network. J Supercomput 77(11):13292–13329. https://doi.org/10.1007/s11227-021-03803-7

    Article  Google Scholar 

  39. Hu C, Liu P, Guo S (2016) Public key encryption secure against related-key attacks and key-leakage attacks from extractable hash proofs J. Ambient Intell Humaniz Comput 7(5):681–692. https://doi.org/10.1007/s12652-015-0329-0

    Article  Google Scholar 

  40. Taloba AI, Elhadad A, El-Aziz RMA, Shahin OR (2021) Prediction of data threats over web medium using advanced blockchain based information security with crypto strategies. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-021-03109-9

    Article  Google Scholar 

  41. Eom S, Huh JH (2018) Group signature with restrictive linkability: minimizing privacy exposure in ubiquitous environment. J Ambient Intell Humaniz Comput 1–11. https://doi.org/10.1007/s12652-018-0698-2

  42. Ramesh D, Mishra R, Trivedi MC (2021) PCS-ABE (t, n): a secure threshold multi authority CP-ABE scheme based efficient access control systems for cloud environment. J Ambient Intell Humaniz Comput 12(10):9303–9322. https://doi.org/10.1007/s12652-020-02643-2

    Article  Google Scholar 

  43. Bojjagani S, Sastry VN, Chen CM, Kumari S, Khan MK (2021) Systematic survey of mobile payments, protocols, and security infrastructure. Springer, Berlin Heidelberg

    Google Scholar 

  44. Alotaibi B, Alotaibi M (2021) Consensus and majority vote feature selection methods and a detection technique for web phishing. J Ambient Intell Humaniz Comput 12(1):717–727. https://doi.org/10.1007/s12652-020-02054-3

    Article  Google Scholar 

  45. Ulukaya S, Sandıkçı EN, Eroğlu Erdem Ç (2022) Consensus and stacking based fusion and survey of facial feature point detectors. J Ambient Intell Humaniz Comput. Doi: https://doi.org/10.1007/s12652-021-03662-3

  46. Li W, Duan P, Su J (2021) The effectiveness of project management construction with data mining and blockchain consensus. J Ambient Intell Humaniz Comput. Doi: https://doi.org/10.1007/s12652-020-02668-7

  47. Formato G, Troiano L, Vaccaro A (2014) Achieving consensus in self-organizing multi agent systems for smart microgrids computing in the presence of interval uncertainty. J Ambient Intell Humaniz Comput 5(6):821–828. https://doi.org/10.1007/s12652-014-0231-1

    Article  Google Scholar 

  48. Pournaghi SM, Bayat M, Farjami Y (2020) MedSBA: a novel and secure scheme to share medical data based on blockchain technology and attribute-based encryption. J Ambient Intell Humaniz Comput 11(11):4613–4641. https://doi.org/10.1007/s12652-020-01710-y

    Article  Google Scholar 

  49. Mayuranathan M, Murugan M, Dhanakoti V (2020) Enhanced security in cloud applications using emerging blockchain security algorithm J. Ambient Intell Humaniz Comput 12(7):6933–6945. https://doi.org/10.1007/s12652-020-02339-7

    Article  Google Scholar 

  50. Rakkini MJJ, Geetha K (2021) Deep learning classification of bitcoin miners and exploration of upper confidence bound algorithm with less regret for the selection of honest mining. J Ambient Intell Humaniz Comput. Doi: https://doi.org/10.1007/s12652-021-03527-9

  51. Mubarakali A, Bose SC, Srinivasan K, Elsir A, Elsier O (2019) Design a secure and efficient health record transaction utilizing block chain (SEHRTB) algorithm for health record transaction in block chain. J Ambient Intell Humaniz Comput. Doi: https://doi.org/10.1007/s12652-019-01420-0

  52. Lee E, Yoon Y (2022) Trusted information project platform based on blockchain for sharing strategy. J Ambient Intell Humaniz Comput 13(3):1575–1585. https://doi.org/10.1007/s12652-019-01421-z

    Article  Google Scholar 

  53. De Luca P, Fiscale S, Landolfi L, Di Mauro A (2019) Distributed genomic compression in MapReduce paradigm. Internet Distrib Comput Syst 11874 LNCS:369–378

  54. Martínez S (2010) Distributed interpolation schemes for field estimation by mobile sensor networks. IEEE Trans Control Syst Technol 18(2):491–500. https://doi.org/10.1109/TCST.2009.2017028

    Article  Google Scholar 

  55. Palamuttam R et al. (2015) SciSpark: Applying in-memory distributed computing to weather event detection and tracking. Proc. 2015 IEEE Int Conf Big Data IEEE Big Data 2015, pp 2020–2026. Doi: https://doi.org/10.1109/BigData.2015.7363983

  56. Casavant TL, Kuhl JG (1988) A taxonomy of scheduling in general-purpose distributed computing systems. IEEE Trans Softw Eng 14(2):141–154. https://doi.org/10.1109/32.4634

    Article  Google Scholar 

  57. Kelkar M, Zhang F, Steven G, Juels A (2020) Order-fairness for byzantine consensus. Adv Cryptol CRYPTO 2020 LNCS 12172:451–480

    Article  MATH  Google Scholar 

  58. Cachin C, Guerraoui R, Rodrigues L (2011) Introduction to reliable and secure distributed programming. Springer Sci Bus Media

  59. Hadzilacos V, Toueg S (1993) Reliable broadcast and related problems. Distrib Syst, pp 97–145

  60. Bracha G, Toueg S (1983) Asynchronous consensus and byzantine protocols in faulty environments. Tech Rep TR 559–83. [Online]. Available: http://ecommons.cornell.edu/handle/1813/6399

Download references

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Radha Rani.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rani, R., Mahato, D.P. A randomized algorithm for the wait-free consensus problem. J Supercomput 79, 3666–3690 (2023). https://doi.org/10.1007/s11227-022-04774-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-022-04774-z

Keywords

Navigation