Skip to main content
Log in

Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components

  • SOFTWARE–HARDWARE SYSTEMS
  • Published:
Cybernetics and Systems Analysis Aims and scope

Abstract

This article considers the ensuring of secure data processing in distributed computer systems (DCSs), which is important for a certain class of computing tasks. An approach to the resource management in DCSs is proposed that makes it possible to take into account, according to user requirements, both the time spent on the execution of a task and the security level of the system resources involved in its execution.

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.

Similar content being viewed by others

References

  1. J. Mariela and H. Curiel, “Wireless Grids: Recent advances in resource and job management,” in: Handbook of Research on Next Generation Mobile Communication Systems, Ch. 12 (an imprint of IGI Global), Information Science Reference, Hershey, PA (2016), pp. 293–320

  2. J. Furthmüller and O. P. Waldhorst, “Survey on Grid computing on mobile consumer devices,” in: Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies, and Applications (in 2 Volumes), N. Antonopoulos, G. Exarchakos, M. Li, and A. Liotta (eds.), Vol. 1, Ch. 13 (an imprint of IGI Global), Information Science Reference, Hershey, PA (2010), pp. 313–337.

  3. H. Hussain, Malik Saif Ur Rehman, A. Hameed, S. U. Khan, G. Bickler, N. Min-Allah, M. B. Qureshi, L. Zhang, W. Yongji, N. Ghani, J. Kolodziej, A. Y. Zomaya, Ch.-Zh. Xu, P. Balaji, A. Vishnu, F. Pinel, J. E. Pecero, D. Kliazovich, P. Bouvry, H. Li, L. Wang, D. Chen, and A. Rayes, “A survey on resource allocation in high performance distributed computing systems,” Parallel Computing, Vol. 39, Iss. 11, 709–736 (2013).

  4. N. Sadashiv and S. M. Dilip Kumar, “Cluster, Grid, and Cloud computing: A detailed comparison,” in: Proc. 6th Intern. Conf. on Computer Science & Education (ICCSE 2011) (2011), pp. 477–482.

  5. I. Brandic and S. Dustdar, “Grid vs Cloud — a technology comparison,” Information Technology Methoden und Innovative Anwendungen der Informatik und Informationstechnik, Vol. 53, Iss. 4, 173–179 (2011).

  6. M. B. Qureshi, M. M. Dehnavi, N. Min-Allah, M. Sh. Qureshi, H. Hussain, I. Rentifis, N. Tziritas, Th. Loukopoulos, S. U. Khan, Cheng-Zhong Xu, and A. Y. Zomaya, “Survey on Grid resource allocation mechanisms,” Journal of Grid Computing, Vol. 12, Iss. 2, 399–441 (2014).

  7. Y. L. Yang, X. G. Peng, and J. F. Cao, “Trust-based scheduling strategy for cloud workflow applications,” Informatica, Vol. 26, No. 1, 159–180 (2015).

    Article  Google Scholar 

  8. H. Liu, A. Abraham, V. Snašel, and S. McLoone, “Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments,” Information Sciences, Vol. 192, 228–243 (2012).

    Article  Google Scholar 

  9. Kaebeh S. B. Yaeghoobi, M. K. Soni, and S. S. Tyagi, “Dynamic and real-time sleep schedule protocols for energy efficiency in WSNs,” International Journal of Computer Network and Information Security (IJCNIS), Vol. 8, No. 1, 9–17 (2016). DOI: 10.5815/ijcnis.2016.01.02.

    Article  Google Scholar 

  10. X. Tang, K. Li, R. Li, and Bh. Veeravalli, “Reliability-aware scheduling strategy for heterogeneous distributed computing systems,” Journal of Parallel and Distributed Computing, Vol. 70, Iss. 9, 941–952 (2010).

  11. X. Wang, C. S. Yeo, R. Buyya, and J. Su, “Optimizing the makespan and reliability for workflow applications with reputation and a look-ahead genetic algorithm,” Future Generation Computer Systems, Vol. 27, Iss. 8, 1124–1134 (2011).

  12. Y. Huang, N. Bessis, P. Norrington, P. Kuonen, and B. Hirsbrunner, “Exploring decentralized dynamic scheduling for grids and clouds using the community-aware scheduling algorithm,” Future Generation Computer Systems, Vol. 29, Iss. 1, 402–415 (2013).

  13. R. Mohan and N. P. Gopalan, “Task assignment for heterogeneous computing tasks using improved iterated greedy algorithm,” International Journal of Computer Network and Information Security (IJCNIS), Vol. 6, No. 7, 50–55 (2014). DOI: 10.5815/ijcnis.2014.07.07.

    Article  Google Scholar 

  14. S. S. Chauhan and R. C. Joshi, “A heuristic for QoS based independent task scheduling in Grid environment,” in: Proc. 5th Intern. Conf. on Industrial and Information Systems (ICIIS 2010), Delhi, India (2010), pp. 102–106.

  15. Tan Fong Ang, Teck Chaw Ling, and Keat Keong Phang, “Adaptive QoS scheduling in a service-oriented grid environment,” Turk. J. Elec. Eng. & Comp. Sci., Vol. 20. No. 3, 413–424 (2012).

    Google Scholar 

  16. J. Conejero, L. Tomás, B. Caminero, and C. Carrión, “QoS provisioning by meta-scheduling via advance within SLA-based Grid environments,” Computing and Informatics, Vol. 31, No. 1, 73–88 (2012).

    Google Scholar 

  17. W. Lin, Ch. Liang, J. Z. Wang, and R. Buyya, “Bandwidth-aware divisible task scheduling for cloud computing,” Software: Practice and Experience, Vol. 44, Iss. 2, 163–174 (2014).

  18. A. Caminero, O. Rana, B. Caminero, and C. Carrión, “Network-aware heuristics for inter-domain meta-scheduling in Grids,” Journal of Computer and System Sciences, Vol. 77, Iss. 2, 262–281 (2011).

  19. J. Jin, J. Luo, A. Song, F. Dong, and R. Xiong, “BAR: An efficient data locality driven task scheduling algorithm for Cloud computing,” in: Proc. 11th IEEE/ACM Intern. Symposium on Cluster, Cloud and Grid Computing (2011), pp. 295–304.

  20. C.-T. Yang, F.-Y. Leu, and S.-Y. Chen, “Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers,” The Journal of Supercomputing, Vol. 52, Iss. 3, 199–223 (2010).

  21. R. McClatchey, A. Anjum, H. Stockinger, A. Ali, I. Willers, and M. Thomas, “Scheduling in data intensive and network aware (DIANA) Grid environments architecture,” URL: https://arxiv.org/ftp/arxiv/papers/0707/0707.0862.pdf.

  22. A. Haquea, S. M. Alhashmia, and R. Parthiban, “A survey of economic models in grid computing,” Future Generation Computer Systems, Vol. 27, Iss. 8, 1056–1069 (2011).

  23. J. Koodziej, S. U. Khan, L. Wang, and A. Y. Zomaya, “Energy efficient genetic-based schedulers in computational grids,” Concurrency Computation: Practice and Experience, Vol. 27, Iss. 4, 809–829 (2015).

  24. H. F. Sheikh, H. Tan, I. Ahmad, and S. Ranka, “Energy- and performance-aware scheduling of tasks on parallel and distributed systems,” ACM Journal on Emerging Technologies in Computing Systems, Vol. 8, Iss. 4, 1–37 (2012).

  25. R. Aydt, D. Gunter, W. Smith, M. Swany, V. Taylor, B. Tierney, and R. Wolski, “A Grid monitoring architecture,” URL: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.18.6602&rep=rep1&type=pdf.

  26. Abebe Tesfahun and D. Lalitha Bhaskari, “Effective hybrid intrusion detection system: A layered approach,” International Journal of Computer Network and Information Security (IJCNIS), Vol. 7, No. 3, 35–41 (2015). DOI: 10.5815/ijcnis.2015.03.05.

    Article  Google Scholar 

  27. M. H. Bhuyan, D. K. Bhattacharyya, and J. K. Kalita, “Network anomaly detection: Methods, systems, and tools,” IEEE Communications Surveys & Tutorials, Vol. 16, No. 1, 303–336 (2014).

    Article  Google Scholar 

  28. V. Ye. Mukhin, A. Ye. Bidkov, and Vu Duc Thinh, “The forming of trust level to the nodes in the distributed computer systems,” in: Proc. XIth Intern. Conf. “Modern Problems of Radio Engineering, Telecommunications and Computer Science TCSET’2012,” Lviv–Slavsko (2012), p. 362.

  29. S. V. Minukhin and A. V. Korovin, “Modeling of GRID resource scheduling by tools of the GRIDSIM package,” Information Processing Systems, No. 3 (93), 62–68 (2011).

  30. I. S. Skiter, O. A. Prelaya, and T. A. Guza, “A review of tools for developing GRID environment models,” in: Proc. Vth Intern. Sci.-Pract. Conf. “Free software in education, science, and business,” Chernihiv National University of Technology, Chernihiv (2014), pp. 28–29.

  31. R. Buyya and M. Murshed, “GridSim: A toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing,” The Journal of Concurrency and Computation: Practice and Experience (CCPE), Wiley Press (2002), URL: http://arxiv.org/abs/cs/0203019.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hu Zhengbing.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 2, March–April, 2017, pp. 168–180.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhengbing, H., Mukhin, V.Y., Kornaga, Y.I. et al. Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components. Cybern Syst Anal 53, 312–322 (2017). https://doi.org/10.1007/s10559-017-9931-9

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10559-017-9931-9

Keywords

Navigation