Skip to main content

CheR: Cheating Resilience in the Cloud via Smart Resource Allocation

  • 763 Accesses

Part of the Lecture Notes in Computer Science book series (LNSC,volume 8352)

Abstract

Cloud computing offers unprecedented ways to split and offload the workload of parallel algorithms to remote computing nodes. However, such remote parties can potentially misbehave, for instance by providing fake computation results in order to save resources. In turn, these erroneous partial results can affect the timeliness and correctness of the overall outcome of the algorithm. The widely successful cloud approach increases the economic feasibility of leveraging computational redundancy to enforce some degree of assurance about the results. However, naïve solutions that dumbly replicate the same computation over several sets of nodes are not cost-efficient.

In this paper, we provide several contributions as for the distribution of workload over (heterogeneous) cloud nodes. In particular, we first formalize the problem of computing a parallel function over a set of nodes; later, we introduce CheR (for Cheating Resilience), a novel approach based upon modelling the assignment of input elements to cloud nodes as a linear integer programming problem aimed at minimizing cost while being resilient against misbehaving nodes. Further, we describe the CheR approach in different scenarios and highlight the novelty with respect to other state-of-the-art solutions. Finally, we present and discuss some experimental results showing the viability and quality of our proposal.

Keywords

  • Smart Resource Allocation
  • Cloud Nodes
  • Input Elements
  • Outsourced Computation
  • CHEERS Statement

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-05302-8_21
  • Chapter length: 14 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-05302-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   99.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.

Notes

  1. 1.

    We assume that the application of \(f\) has the same cost and complexity for each input.

  2. 2.

    The ordering of the performed operations does not take actual time into consideration.

  3. 3.

    Given that the complexity of the LP model is the same.

References

  1. Cornell-University: Red cloud with MATLAB. http://www.cac.cornell.edu/wiki/index.php?title=Red_Cloud_with_MATLAB

  2. Nimbis: Cloud services for mathematica. https://www.nimbisservices.com/marketplace/wolfram-research/mathematica-clouds

  3. D’Angelo, G.: Parallel and distributed simulation from many cores to the public cloud. In: 2011 International Conference on High Performance Computing and Simulation (HPCS), pp. 14–23 (2011)

    Google Scholar 

  4. Church, P., Wong, A., Brock, M., Goscinski, A.: Toward exposing and accessing HPC applications in a SaaS cloud. In: Proceedings of the 2012 IEEE 19th International Conference on Web Services, ICWS ’12, pp. 692–699. IEEE Computer Society, Washington, DC (2012)

    Google Scholar 

  5. Groce, A., Katz, J., Thiruvengadam, A., Zikas, V.: Byzantine agreement with a rational adversary. In: Czumaj, A., Mehlhorn, K., Pitts, A., Wattenhofer, R. (eds.) ICALP 2012, Part II. LNCS, vol. 7392, pp. 561–572. Springer, Heidelberg (2012)

    Google Scholar 

  6. Mahdavi-Amiri, N., Nasseri, S.H.: Duality results and a dual simplex method for linear programming problems with trapezoidal fuzzy variables. Fuzzy Sets Syst. 158(17), 1961–1978 (2007)

    CrossRef  MATH  MathSciNet  Google Scholar 

  7. Martins, F.S., Andrade, R.M., dos Santos, A.L., Schulze, B., de Souza, J.N.: Detecting misbehaving units on computational grids. Concurr. Comput.: Pract. Exper. 22(3), 329–342 (2010)

    Google Scholar 

  8. Golle, P., Mironov, I.: Uncheatable distributed computations. In: Naccache, D. (ed.) CT-RSA 2001. LNCS, vol. 2020, pp. 425–440. Springer, Heidelberg (2001)

    Google Scholar 

  9. Gennaro, R., Gentry, C., Parno, B.: Non-interactive verifiable computing: outsourcing computation to untrusted workers. In: Rabin, T. (ed.) CRYPTO 2010. LNCS, vol. 6223, pp. 465–482. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  10. Makhorin, A.O.: GLPK GNU Linear Programming Kit. http://www.gnu.org/software/glpk/glpk.html

  11. Amazon: Amazon web services. http://aws.amazon.com

  12. Moser, H.: Towards a real-time distributed computing model. Theor. Comput. Sci. 410(6–7), 629–659 (2009)

    CrossRef  MATH  Google Scholar 

  13. Lombardi, F., Di Pietro, R., Soriente, C.: CReW: cloud resilience for Windows guests through monitored virtualization. In: Proceedings of the 2010 29th IEEE Symposium on Reliable Distributed Systems, SRDS ’10, pp. 338–342. IEEE Computer Society, Washington, DC (2010)

    Google Scholar 

  14. Das Sarma, A., Holzer, S., Kor, L., Korman, A., Nanongkai, D., Pandurangan, G., Peleg, D., Wattenhofer, R.: Distributed verification and hardness of distributed approximation. In: Proceedings of the 43rd Annual ACM Symposium on Theory of Computing, STOC ’11, pp. 363–372. ACM, New York (2011)

    Google Scholar 

  15. Cheon, E., Kim, M., Kuk, S., Kim, H.S.: A regional matchmaking technique for improving efficiency in volunteer computing environment. In: Proceedings of the 1st ACIS/JNU International Conference on Computers, Networks, Systems and Industrial Engineering, CNSI ’11, pp. 285–289. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  16. Costa, P., Pasin, M., Bessani, A.N., Correia, M.: Byzantine fault-tolerant mapreduce: faults are not just crashes. In: Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science, CLOUDCOM ’11, pp. 32–39. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  17. Koeppe, F., Schneider, J.: Do you get what you pay for? using proof-of-work functions to verify performance assertions in the cloud. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom), pp. 687–692, 30 November 2010-3 December 2010

    Google Scholar 

  18. Dwork, C., Naor, M.: Pricing via processing or combatting junk mail. In: Brickell, E.F. (ed.) CRYPTO 1992. LNCS, vol. 740, pp. 139–147. Springer, Heidelberg (1993)

    Google Scholar 

  19. Popa, R.A., Lorch, J.R., Molnar, D., Wang, H.J., Zhuang, L.: Enabling security in cloud storage slas with cloudproof. In: Proceedings of the 2011 USENIX Conference on USENIX Annual Technical Conference, USENIXATC’11, p. 31. USENIX Association, Berkeley (2011)

    Google Scholar 

  20. Kotla, R., Alvisi, L., Dahlin, M., Clement, A., Wong, E.: Zyzzyva: speculative byzantine fault tolerance. ACM Trans. Comput. Syst. 27(4), 7:1–7:39 (2010)

    Google Scholar 

  21. Xin, S., Zhao, Y., Li, Y.: Property-based remote attestation oriented to cloud computing. In: Proceedings of the 7th International Conference on Computational Intelligence and Security, CIS ’11, pp. 1028–1032. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  22. Luo, Y., Manivannan, D.: Hope: a hybrid optimistic checkpointing and selective pessimistic message logging protocol for large scale distributed systems. Future Gener. Comput. Syst. 28(8), 1217–1235 (2012)

    CrossRef  Google Scholar 

  23. Ahrendt, W., Dylla, M.: A system for compositional verification of asynchronous objects. Sci. Comput. Program. 77(12), 1289–1309 (2012)

    CrossRef  MATH  Google Scholar 

  24. Beimel, A., Lindell, Y., Omri, E., Orlov, I.: 1/p-secure multiparty computation without honest majority and the best of both worlds. In: Rogaway, P. (ed.) CRYPTO 2011. LNCS, vol. 6841, pp. 277–296. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  25. Parno, B., Gentry, C., Howell, J., Raykova, M.: Pinocchio: nearly practical verifiable computation. In: Proceedings of the 34th IEEE Symposium on Security and Privacy (2013)

    Google Scholar 

  26. Groenwold, A.A.: Positive definite separable quadratic programs for non-convex problems. Struct. Multidiscip. Optim. 46(6), 795–802 (2012)

    CrossRef  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work has been partially supported by the TENACE PRIN Project (n.20103P34XC) funded by the Italian Ministry of Education, University and Research.

The research leading to these results has received funding from the EU Seventh Framework Programme (FP7/2007-2013) under grant n. 256980 (NESSoS), n. 257930 (Aniketos), and EIT ICT Labs activity 13083.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daniele Sgandurra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Roberto, D.P., Lombardi, F., Martinelli, F., Sgandurra, D. (2014). CheR: Cheating Resilience in the Cloud via Smart Resource Allocation. In: Danger, J., Debbabi, M., Marion, JY., Garcia-Alfaro, J., Zincir Heywood, N. (eds) Foundations and Practice of Security. FPS 2013. Lecture Notes in Computer Science(), vol 8352. Springer, Cham. https://doi.org/10.1007/978-3-319-05302-8_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05302-8_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05301-1

  • Online ISBN: 978-3-319-05302-8

  • eBook Packages: Computer ScienceComputer Science (R0)