Skip to main content
Log in

The \(k\)-Set consensus problem with weight consideration

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

Abstract

In the cloud computing environment, files are duplicated into several copies for storage at different locations to increase their access efficiency and fault tolerance. However, there may exist malicious processors in the cloud computing environment. How to ensure that fault-free processors coordinate to find appropriate locations to store these duplicated files without influence from malicious processors is an important issue. In this paper, we propose a consensus algorithm to assist fault-free processors in reaching a consensus on where to store the duplicated files in the presence of malicious processors. In this paper, we will extend the classical consensus problem to a new type of consensus problem called the \(k\)-Set consensus problem with weight consideration (\(k\)-SetW problem). This problem is integrated with the concepts of weight and \(k\)-Set. In other words, each processor in this problem is allowed to have multiple initial values (i.e., the expected locations for the duplicated files) and set the weight for each initial value. The weighted value shows the processor’s preference for an initial value. Regarding the consensus, this problem does not require agreement among all fault-free processors on a single consensus value. It allows coexistence of multiple consensus values as long as the number of consensus values is not greater than \(k\) (i.e., the maximum number of duplicated files). By solving the \(k\)-SetW problem, we can help fault-free processors determine the locations for storing the duplicates of at most \(k\) copies based on their preferences in the presence of malicious processors.

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

Access this article

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
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. White T (2009) Hadoop: the definitive guide, MapReduce for the cloud. O’Reilly Media, New York

  2. Afrati FN, Ullman JD (2011) Optimizing multiway joins in a map-reduce environment. IEEE Trans Knowl Data Eng 23(9)

  3. Jiang D, Tung AKH, Chen G (2011) MAP-JOIN-REDUCE: toward scalable and efficient data analysis on large clusters. IEEE Trans Knowl Data Eng 23(9)

  4. Attiya H, Welch J (2004) Distributed computing—fundamentals, simulation and advanced topics, 2nd edn. Wiley, New York, pp 414

  5. Borran F, Hutle M, Santos N, Schiper A (2012) Quantitative analysis of consensus algorithms. IEEE Trans Depend Secure Comput 9(2):236–249

    Article  Google Scholar 

  6. Silberschatz A, Galvin PB, Gagne G (2009) Operating system concepts, 8th edn. Wiley, New York

  7. Barborak M, Malek M, Dahubra A (1993) The consensus problem in fault-tolerant computing. ACM Comput Surv 25(2):171–220

    Article  Google Scholar 

  8. Attiya H, Bar-noy A, Dolev D, Peleg D, Reischuk R (1990) Renaming in an asynchronous environment. J ACM 37(3):524–548

    Article  MathSciNet  MATH  Google Scholar 

  9. Chaudhuri S, Herlihy M, Lynch N, Tuttle M (2000) Tight bounds for \(k\)-set agreement. J ACM 47(5):912–943

    Article  MathSciNet  Google Scholar 

  10. Parvedy PR, Raynal M, Travers C (2005) Decision optimal early-stopping \(k\)-set agreement in synchronous systems prone to send omission failures. In: Proceedings of the 11th Pacific Rim international symposium on dependable computing

  11. Saks M, Zaharoglou F (2000) Wait-free \(k\)-set agreement is impossible: the topology of public knowledge. SIAM J Comput 29(5):1449–1483

    Article  MathSciNet  MATH  Google Scholar 

  12. Garg VK, Bridgman J (2011) The weighted Byzantine agreement problem. In: Proceedings of the IEEE parallel and distributed processing symposium

  13. Berman P, Garay JA (1989) Asymptotically optimal distributed consensus. Proceedings of the international colloquium on automata, languages and programming, Copenhagen

    Google Scholar 

  14. Berman P, Garay JA, Perry KJ (1989) Towards optimal distributed consensus. In: Proceedings of the annual symposium on foundations of computer science, pp 410–415

  15. Fisher M, Lynch N (1982) A lower bound for the time to assure interactive consistency. Inf Process Lett 14(3):183–186

    Article  Google Scholar 

  16. Fischer M, Lynch N, Paterson M (1985) Impossibility of distributed consensus with one faulty process. J ACM 32(2):378–382

    Article  MathSciNet  Google Scholar 

  17. Biely M, Hutle M (2011) Consensus when all processes may be Byzantine for some time. Theor Comput Sci 412:4260–4272

    Article  MathSciNet  MATH  Google Scholar 

  18. Cheng CF, Tsai KT (2012) From immediate agreement to eventual agreement: early stopping agreement protocol for dynamic networks with malicious faulty processors. J Supercomput 62(2):874–894

    Article  Google Scholar 

  19. Ma ZS, Krings AW (2011) Dynamic hybrid fault modeling and extended evolutionary game theory for reliability, survivability and fault tolerance analyses. IEEE Trans Reliab 60(1)

  20. Bar-Noy A, Dolev D, Dwork C, Raymond Strong H (1992) Shifting gears: changing algorithms on the fly to expedite Byzantine agreement. Inf Comput 97(2):205–233

    Article  MATH  Google Scholar 

Download references

Acknowledgments

C. F. Cheng’s research was sponsored by the National Science Council of Taiwan, ROC, under Grant NSC102-2221-E-032-026.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chien-Fu Cheng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheng, CF., Liao, HC. The \(k\)-Set consensus problem with weight consideration. J Supercomput 71, 144–161 (2015). https://doi.org/10.1007/s11227-014-1291-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-014-1291-x

Keywords

Navigation