Skip to main content

Advertisement

Springer Nature Link
Log in

STEP: A Concomitant Protocol for Real Time Applications

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In distributed real-time database system, utilizing a priority inheritance mechanism may help in reducing the priority inversion duration of a conflicting (and waiting) high priority transaction. However, mere integration of the priority inheritance scheme with classic 2PC is not enough and may lead to performance degradation. The two main problems that arise because of such integration are considerably longer ‘Priority-Inherit’ message dissemination time and extra message overhead. In addition, the explosion of priority inheritance events in the system might lead to the increased miss percentage for high-priority transactions. To address the above-mentioned problems, a Sophisticated Time and message utilization centered Priority inheritance (STEP) concomitant protocol is designed which brings down the overhead (time & message) by simply requiring of single round intelligent message transfer and eliminates priority de-boosting part of the general priority inheritance mechanism. Moreover, it also keeps a check on the no. of priority inheritance events occurrences with the help of real-time monitoring of priority inversions’ percentage in the system and thereby makes sure that high priority transaction miss percentage does not increase in an uncontrolled manner. The extensive performance study suggests that STEP protocol performs considerably well compared to the existing state-of-the-art protocols.

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

Access this article

Log in via an institution

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.

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
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  1. Shanker, U., Misra, M., & Sarje, A. (2006). Some performance issues in distributed real-time database systems. In Proc. VLDB Ph.D. Work, Conv. Exhib. Cent. (COEX), Seoul, Korea.

  2. Ezechiel, K. K., Kant, S., & Agarwal, R. (2019). A synchronizer-mediator for lazy replicated databases over a decentralized P2P architecture. In 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (pp. 199-213). IEEE.

  3. Pandey, S., & Shanker, U. (2020). Transaction scheduling protocols for controlling priority inversion: A review. Computer Science Review, 35, 100215.

    Article  MathSciNet  Google Scholar 

  4. Gupta, A. K., & Shanker, U. (2020). OMCPR: Optimal mobility aware cache data pre-fetching and replacement policy using spatial K-anonymity for LBS. Wireless Personal Communications, 114(2), 949–973.

    Article  Google Scholar 

  5. Shanker, U., Misra, M., & Sarje, A. K. (2008). Distributed real time database systems: Background and literature review. International Journal of Distributed and Parallel Databases, 23(02), 127–149.

    Article  Google Scholar 

  6. Pandey, S., & Shanker, U. (2021). Performance issues in scheduling of real-time transactions. International Conference on Database Systems for Advanced Applications (DASFAA-2021), Taipei, Taiwan (pp. 638–642). Springer.

    Google Scholar 

  7. Chauhan, N., & Tripathi, S. (2021). Optimal admission control policy based on memetic algorithm in distributed real time database system. Wireless Personal Communications, 117(2), 1123–1141.

    Article  Google Scholar 

  8. Pandey, S., & Shanker, U. (2018). Priority inversion in DRTDBS: challenges and resolutions. In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, (CoDS-COMAD '18) (pp. 305-309).

  9. Kim, Y. K., & Son, S. H. (1995). Predictability and consistency in real-time database systems. Advances in real-time systems, pp. 509-531.

  10. Arun, A., Pandey, S., & Shanker, U. (2021). A multi-replica centered commit protocol for distributed real-time and embedded applications. International Journal of System Dynamics Applications (IJSDA), 10(4), 1–19.

    Article  Google Scholar 

  11. Aldarmi, S. A. (1999). Scheduling soft-deadline real-time transactions. Ph.D. Thesis, University of York.

  12. Shanker, U., Misra, M., & Sarje, A. K. (2001). Hard real-time distributed database systems: Future directions. In Proceedings of All India Seminar on Recent Trends in Computer Communication Networks, Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, India, pp.172-177.

  13. Pandey, S., & Shanker, U. (2021). MDTF: A most dependent transactions first priority assignment heuristic. In R. M. Mehdi Khosrow-Pour (Ed.), Encyclopedia of organizational knowledge, administration, and technology (pp. 742–756). IGI Global

    Chapter  Google Scholar 

  14. Singh, P. K., & Shanker, U. (2017). Priority heuristic in mobile distributed real time database using optimistic concurrency control. In 2017 23RD Annual International Conference in Advanced Computing and Communications (ADCOM), Bangalore, India, (pp. 44-49). IEEE.

  15. Lam, K. Y. (1994). Concurrency control in distributed real time database systems. PhD Thesis.

  16. Lam, K.-Y., Hung, S.-L., & Son, S. H. (1997). On eusing real-time static locking protocols for distributed real-time databases. Real-Time Systems, 13(02), 141–166.

    Article  Google Scholar 

  17. Pandey, S., & Shanker, U. (2020). RAPID: A real time commit protocol. Journal of King Saud University—Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2020.04.006

    Article  Google Scholar 

  18. Shanker, U., Misra, M., & Sarje, A. K. (2005). A memory efficient fast distributed real time commit protocol. International Workshop on Distributed Computing (pp. 500–505). Springer.

    Google Scholar 

  19. Pandey, S., & Shanker, U. (2018). On using priority inheritance-based distributed static two-phase locking protocol. Advances in data and information sciences (pp. 179–188). Springer.

    Chapter  Google Scholar 

  20. Pandey, S., & Shanker, U. (2018). CART: A real-time concurrency control protocol. In Proceedings of the 22nd International Database Engineering & Applications Symposium (IDEAS 2018), Bipin C. Desai, Jun Hong, and Richard McClatchey (Eds.). ACM, New York, NY, USA., June 18-20, 2018

  21. Yu, P. S., Wu, K.-L., Lin, K.-J., & Son, S. H. (1994). On real-time databases : Concurrency control and scheduling. Proceedings of the IEEE, 82(01), 140–157.

    Article  Google Scholar 

  22. Chaudhry, N., & Yousaf, M. M. (2021). Concurrency control for real-time and mobile transactions: Historical view, challenges, and evolution of practices. Concurrency and Computation: Practice and Experience. https://doi.org/10.1002/cpe.6549

    Article  Google Scholar 

  23. Pandey, S., & Shanker, U. (2020). RACE: A concurrency control protocol for time-constrained transactions. Arabian Journal for Science and Engineering, 45, 10131–10146.

    Article  Google Scholar 

  24. Pandey, S., & Shanke, U. (2020). Causes, effects, and consequences of priority inversion in transaction processing. Handling Priority Inversion in Time-Constrained Distributed Databases (pp. 1–13). IGI Global.

    Google Scholar 

  25. Sha, L., Rajkumar, R., Son, S. H., & Chang, C. H. (1991). A real-time locking protocol. IEEE Transactions on Computers, 40(07), 793–800.

    Article  Google Scholar 

  26. Abbott, R. K., & Molina, H. G. (1992). Scheduling real-time transactions: A performance evaluation. ACM Transactions on Database Systems, 17(03), 513–560.

    Article  Google Scholar 

  27. Lam, K., Pang, C. L., Son, S., & Cao, J. (1999). Resolving executing-committing conflicts in distributed real-time database systems. The Computers Journal, 42(08), 674–692.

    Article  Google Scholar 

  28. Yu, P. S., Dias, D. M., & Lavenberg, S. S. (1993). On the analytical modeling of database concurrency control. Journal of the ACM, 40(4), 831–872.

    Article  Google Scholar 

  29. Gupta, R., Haritsa, J., Ramamritham, K., & Seshadri, S. (1996). Commit processing in distributed real-time database systems. In 17th IEEE Real-Time Systems Symposium (pp. 220-229). IEEE.

  30. Haritsa, J. R., Ramamritham, K., & Gupta, R. (2000). The PROMPT real-time commit protocol. IEEE Transactions on Parallel and Distributed Systems, 11(02), 160–181.

    Article  Google Scholar 

  31. Shanker, U., Misra, M., & Sarje, A. K. (2006). SWIFT—A new real time commit protocol. Distributed and Parallel Databases, 20(01), 29–56.

    Article  Google Scholar 

  32. Pandey, S., & Shanker, U. (2018). IDRC: A distributed real-time commit protocol. Procedia Computer Science, 125, 290–296.

    Article  Google Scholar 

  33. Pandey, S., & Shanker, U. (2021). EDRC: An early data lending-based real-time commit protocol. Encyclopedia of Information Science and Technology (5th ed., pp. 800–814). IGI Global.

    Chapter  Google Scholar 

  34. Pandey, S., & Shanker, U. (2018). A one phase priority inheritance commit protocol. International Conference on Distributed Computing and Internet Technology (pp. 288–294). Springer.

    Chapter  Google Scholar 

  35. Sha, L., Rajkumar, R., & Lehoczky, J. P. (1990). Priority inheritance protocols: An approach to real-time synchronization. IEEE Transactions on Computers, 39(9), 1175–1185.

    Article  MathSciNet  Google Scholar 

  36. Ulusoy, O. (1995). A study of two transaction-processing architectures for distributed real-time data base systems. The Journal of Systems and Software, 31(02), 97–108.

    Article  Google Scholar 

  37. Taina, J., & Son, S. H. (1999). Towards a general real-time database simulator software library. IFAC Proceedings, 32(01), 75–80.

    Google Scholar 

  38. Ulusoy, Ö., & Belford, G. G. (1993). Real-time transaction scheduling in database systems. Information Systems, 18(08), 559–580.

    Article  Google Scholar 

  39. Pandey, S., & Shanker, U. (2020). A contention aware EQS priority assignment heuristic for cohorts in DRTDBS. The Journal of Supercomputing, 77, 6629–6663.

    Article  Google Scholar 

  40. Stankovic, J., & Zhao, W. (1988). On real-time transactions. ACM Sigmod Record, 17(1), 4–18.

    Article  Google Scholar 

  41. Pease, M., Shostak, R., & Lamport, L. (1980). Reaching agreement in the presence of faults. Journal of the ACM, 27(2), 228–234.

    Article  MathSciNet  Google Scholar 

  42. D. Skeen, "Nonblocking commit protocols," in Proceedings of the ACM SIGMOD international conference on Management of data, pp. 133–142, 1981.

  43. Dwork, C., & Skeen, D. (1983). The inherent cost of nonblocking commitment. In Proceedings of the second annual ACM symposium on Principles of distributed computing (pp. 1-11).

  44. Van Renesse, R., & Altinbuken, D. (2015). Paxos made moderately complex. ACM Computing Surveys (CSUR), 47(3), 1–36.

    Article  Google Scholar 

  45. Lee, V. C. S., Lam, K.-W., & Hung, S.-L. (2002). Concurrency control for mixed transactions in real-time databases. IEEE Transactions on Computers, 51(7), 821–834.

    Article  Google Scholar 

  46. Pandey, A. K., Pandey, S., & Shanker, U. (2019). LIFT-A new linear two-phase commit protocol. In Proceedings of 25th annual international conference on advanced computing and communications (ADCOM 2019) at IIIT Bangalore.

  47. Pandey, S., Pandey, A. K., & Shanker, U. (2020). SP-LIFT: A dserial parallel linear and fast-paced recovery-centered transaction commit protocol. SN Computer Science, 1, 1–10.

    Article  Google Scholar 

  48. Chaudhry, N., & Yousaf, M. (2020). Architectural assessment of NoSQL and NewSQL systems. Distrib Parallel Databases, 38, 881–926.

    Article  Google Scholar 

  49. Chaudhry, N., Yousaf, M., & Khan, M. (2020). Indexing of real time geospatial data by IoT enabled devices: Opportunities, challenges and design considerations. Journal of Ambient Intelligence and Smart Environments, 12(4), 281–312.

    Article  Google Scholar 

  50. Singh, R. K., Pandey, S., & Shanker, U. (2019). A non-database operations aware priority ceiling protocol for hard real-time database systems. In 2019 10th International Conference on Computing, Communication and Networking Technologies, IIT, Kanpur, India, July 6-8. IEEE.

  51. Chaudhry, N., & Yousaf, M. M. (2018). Consensus algorithms in blockchain: Comparative analysis, challenges and opportunities. In 2018 12th International Conference on Open Source Systems and Technologies (ICOSST) (pp. 54-63). IEEE.

Download references

Funding

The financial support from the Council of Scientific and Industrial Research (CSIR), New Delhi, India—under Grant No. 1061461137—during this research work is appreciated.

Author information

Author notes

  1. Sarvesh Pandey

    Present address: Banaras Hindu University, Varanasi, India

Authors and Affiliations

  1. Department of Computer Science and Engineering, M.M.M. University of Technology, Gorakhpur, 273 010, India

    Sarvesh Pandey & Udai Shanker

Authors
  1. Sarvesh Pandey
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Udai Shanker
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Sarvesh Pandey.

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

Pandey, S., Shanker, U. STEP: A Concomitant Protocol for Real Time Applications. Wireless Pers Commun 122, 3795–3832 (2022). https://doi.org/10.1007/s11277-021-09112-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-09112-9

Keywords