A Priority Heuristic Policy in Mobile Distributed Real-Time Database System

  • Prakash Kumar SinghEmail author
  • Udai Shanker
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 38)


In fast processing new technology, to provide priority scheduling among different running transactions is a challenging part of research in wireless environment. It incorporates a mechanism to assign priority among transaction to maintain a sequence of execution. Priority heuristics are the backbone of a transaction scheduling approach in real-time systems. It is one of the sophisticated tasks which heavily affect the overall performance of mobile distributed real-time database system (MDRTDBS). Priority heuristics have been developed for centralized and distributed real-time database systems where cohorts or sub-transaction executed in sequential/parallel manner; however, these heuristics may not fit well for the MDRTDBS where sub-transactions are performing parallel execution and face a lot of wireless environment challenges. In this paper, a priority heuristic has proposed which integrates the concept of number of write locks and the variable size of data items. Further, simulation study has been done to evaluate performance of proposed priority heuristics with earliest deadline first and heuristic based on number of locks required.


Real-time Transaction Priority heuristic Mobile distributed database 


  1. 1.
    Abbott RK, Molina HG (1992) Scheduling real time transactions: A performance evaluation. ACM Trans Database Syst 17(3):513–560CrossRefGoogle Scholar
  2. 2.
    Haritsa JR, Carey MJ, Livny M (1992) Data access scheduling in firm real-time database systems. J Real-Time Syst 4(3):203–242CrossRefGoogle Scholar
  3. 3.
    Lam KY, Lee VCS, Hung SL, Kao BCM (1997) Priority assignment in distributed real-time databases using optimistic concurrency control. IEE Proc-Comput Digital Tech 144(5):324–330CrossRefGoogle Scholar
  4. 4.
    Lee VCS, Lam KY, Kao BCM, Lam KW, Hung SL (1996) Priority assignment for sub-transaction in distributed real-time databases. In: First international workshop on real-time database systems (1996)Google Scholar
  5. 5.
    Lam KY (1994) Concurrency control in distributed real-time database systems. Ph.D. thesis, Department of Computer Science, City University of Hong Kong, Hong KongGoogle Scholar
  6. 6.
    Shanker U, Misra M, Sarje AK (2006) SWIFT: a new real time commit protocol. Distrib Parallel Databases 20(1):29–56CrossRefGoogle Scholar
  7. 7.
    Shanker U, Misra M, Sarje AK (2008) Distributed real time database systems: background and literature review. Int J Distrib Parallel Databases 23(2):127–149CrossRefGoogle Scholar
  8. 8.
    Lam KY, Ku TW, Tsang WH, Law GCK (2000) Concurrency control in mobile distributed real-time database. J Inf Syst 25(4), 261–286Google Scholar
  9. 9.
    Lei X, Zhao Y, Chen S, Yuan X (2009) Concurrency control in mobile distributed real-time database systems. J Parallel Distrib Comput 69:866–876CrossRefGoogle Scholar
  10. 10.
    Kao B, Molina HG (1993) Deadline assignment in a distributed soft real-time system. In: Proceedings 13th international conference on distributed computing systems, pp 428–437Google Scholar
  11. 11.
    Xiangdong L, Yuelong Z, Songqiao C, Xiaoli Y (2010) A multiversion optimistic concurrency control protocol in mobile broadcast environments. Int J Comput Appl 32(3):261–266Google Scholar
  12. 12.
    Shanker U, Misra M, Sarje AK (2005) Priority assignment heuristic to cohorts executing in parallel. In: Proceedings of the 9th WSEAS international conference on computers, World Scientific and Engineering Academy and Society (WSEAS), pp 1–6Google Scholar
  13. 13.
    Singh PK, Shanker U (2017) Priority heuristic in mobile distributed real time database using optimistic concurrency control. ADCOM 2017Google Scholar
  14. 14.
    Lee VCS, Wu X, Ng JKY (2006) Scheduling real-time requests in on-demand data broadcast environment. J Real-Time Syst 34(2):83–99CrossRefGoogle Scholar
  15. 15.
    Pitoura E, Chrysanthis PK (1999) Scalable processing of readonly transactions in broadcast push. In: Proceedings of the 19th IEEE international conference on distributed computing system, pp 432–439Google Scholar
  16. 16.
    Lee VCS, Lam KW, Son SH (2000) Real-time transaction processing with partial validation at mobile clients. In: Proceedings of seventh international conference on real-time computing systems and applications. IEEE, pp 473–477Google Scholar
  17. 17.
    Lee VCS, Lam KW, Son SH, Chan EYM (2002) On transaction processing with partial validation and timestamp ordering in mobile broadcast environments. J IEEE Trans Comput 51(10):1196–1211MathSciNetCrossRefGoogle Scholar
  18. 18.
    Lee VCS, Lam KW, Kuo TW (2004) Efficient validation of mobile transactions in wireless environments. J Syst Softw 69(1):183–193CrossRefGoogle Scholar
  19. 19.
    Herman G, Lee KC, Weinrib A (1987) The datacycle architecture for very high throughput database systems. Proc ACM SIGMOD Record 16(3):97–103CrossRefGoogle Scholar
  20. 20.
    Shanmugasundaram J, Nithrakashyap A, Sivasankaran R, Ramamritham K (1999) Efficient concurrency control for broadcast environments. ACM SIGMOD Record 28(2):85–96CrossRefGoogle Scholar
  21. 21.
    Park S, Jung S (2009) An energy-efficient mobile transaction processing method using random back-off in wireless broadcast environments. J Syst Softw 82(12):2012–2022CrossRefGoogle Scholar
  22. 22.
    Hameed S, Vaidya NH (1999) Efficient algorithms for scheduling data broadcast. ACM/Baltzer J Wireless Network 5(3):183–193CrossRefGoogle Scholar
  23. 23.
    Zipf PGK (1949) Human behavior and the principle of least effort. Addison-Wesley, MassachusettsGoogle Scholar
  24. 24.
    Qin B, Liu Y (2003) High performance distributed real time commit protocol. J Syst Softw, pp 1–8 (Elsevier Science Inc)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringMMM University of TechnologyGorakhpurIndia

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