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Real-Time Systems

, Volume 44, Issue 1–3, pp 1–25 | Cite as

DESH: overhead reduction algorithms for deferrable scheduling

  • Ming Xiong
  • Song HanEmail author
  • Deji Chen
  • Kam-Yiu Lam
  • Shan Feng
Article

Abstract

Although the deferrable scheduling algorithm for fixed priority transactions (DS-FP) has been shown to be a very effective approach for minimizing real-time update transaction workload, it suffers from its on-line scheduling overhead. In this work, we propose two extensions of DS-FP to minimize the on-line scheduling overhead. The proposed algorithms produce a hyperperiod from DS-FP so that the schedule generated by repeating the hyperperiod infinitely satisfies the temporal validity constraint of the real-time data. The first algorithm, named DEferrable Scheduling with Hyperperiod by Schedule Construction (DESH-SC), searches the DS-FP schedule for a hyperperiod. The second algorithm, named DEferrable Scheduling with Hyperperiod by Schedule Adjustment (DESH-SA), adjusts the DS-FP schedule in an interval to form a hyperperiod. Our experimental results demonstrate that while both DESH-SC and DESH-SA can reduce the scheduling overhead of DS-FP, DESH-SA outperforms DESH-SC by accommodating significantly more update transactions in the system. Moreover, DESH-SA can also achieve near-optimal update workload.

Keywords

Real-Time databases Temporal validity constraint Fixed priority scheduling Deferrable scheduling 

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References

  1. Burns A, Davis R (1996) Choosing task periods to minimise system utilisation in time triggered systems. Inf Process Lett 58:223–229 zbMATHCrossRefGoogle Scholar
  2. Chen D, Mok AK (2004) Scheduling similarity-constrained real-time tasks. In: ESA/VLSI, pp 215–221 Google Scholar
  3. Chetto H, Chetto M (1989) Some results of the earliest deadline scheduling algorithm. IEEE Trans Softw Eng 15(10):1261–1269 CrossRefMathSciNetGoogle Scholar
  4. Gerber R, Hong S, Saksena M (1994) Guaranteeing end-to-end timing constraints by calibrating intermediate processes. In: IEEE real-time systems symposium, December 1994 Google Scholar
  5. Gustafsson T, Hansson J (2004a) Data management in real-time systems: a case of on-demand updates in vehicle control systems. In: IEEE real-time and embedded technology and applications symposium, pp 182–191 Google Scholar
  6. Gustafsson T, Hansson J (2004b) Dynamic on-demand updating of data in real-time database systems. In: ACM SAC Google Scholar
  7. Han CC, Lin KJ, Liu JW-S (1995) Scheduling jobs with temporal distance constraints. SIAM J Comput 24(5):1104–1121 zbMATHCrossRefMathSciNetGoogle Scholar
  8. Kang KD, Son S, Stankovic JA, Abdelzaher T (2002) A QoS-sensitive approach for timeliness and freshness guarantees in real-time databases. In: EuroMicro real-time systems conference, June 2002 Google Scholar
  9. Kuo T, Mok AK (1992) Real-time data semantics and similarity-based concurrency control. In: IEEE real-time systems symposium, December 1992 Google Scholar
  10. Kuo T, Mok AK (1993) SSP: a semantics-based protocol for real-time data access. In: IEEE real-time systems symposium, December 1993 Google Scholar
  11. Ho S, Kuo T, Mok AK (1997) Similarity-based load adjustment for real-time data-intensive applications. In: IEEE real-time systems symposium Google Scholar
  12. Lam KY, Xiong M, Liang B, Guo Y (2004) Statistical quality of service guarantee for temporal consistency of real-time data objects. In: IEEE real-time systems symposium Google Scholar
  13. Leung J, Whitehead J (1982) On the complexity of fixed-priority scheduling of periodic real-time tasks. Perform Eval 2:237–250 zbMATHCrossRefMathSciNetGoogle Scholar
  14. Liu CL, Layland J (1973) Scheduling algorithms for multiprogramming in a hard real-time environment. J ACM 20(1) Google Scholar
  15. Locke D (1997) Real-time databases: real-world requirements. In: Bestavros A, Lin K-J, Son SH (eds) Real-time database systems: issues and applications. Kluwer Academic, Dordrecht, pp 83–91 Google Scholar
  16. Ramamritham K (1993) Real-time databases. Distrib Parallel Databases 1(1993):199–226 CrossRefGoogle Scholar
  17. Ramamritham K (1996) Where do time constraints come from and where do they go? Int J Database Manag 7(2):4–10 Google Scholar
  18. Song X, Liu JWS (1995) Maintaining temporal consistency: pessimistic vs. optimistic concurrency control. IEEE Trans Knowl Data Eng 7(5):786–796 CrossRefGoogle Scholar
  19. Xiong M, Ramamritham K (2004) Deriving deadlines and periods for real-time update transactions. IEEE Trans Comput 53(5):567–583 CrossRefGoogle Scholar
  20. Xiong M, Ramamritham K, Stankovic JA, Towsley D, Sivasankaran RM (2002) Scheduling transactions with temporal constraints: exploiting data semantics. IEEE Trans Knowl Data Eng 14(5):1155–1166 CrossRefGoogle Scholar
  21. Xiong M, Han S, Lam KY (2005) A deferrable scheduling algorithm for real-time transactions maintaining data freshness. In: IEEE real-time systems symposium Google Scholar
  22. Xiong M, Han S, Chen D (2006) Deferrable scheduling for temporal consistency: schedulability analysis and overhead reduction. In: IEEE international conference on embedded and real-time computing systems and applications, August 2006 Google Scholar
  23. Xiong M, Han S, Lam KY, Chen D (2008) Deferrable scheduling for maintaining real-time data freshness: algorithm, analysis and results. IEEE Trans Comput 57(7):952–964 CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Ming Xiong
    • 1
  • Song Han
    • 2
    Email author
  • Deji Chen
    • 3
  • Kam-Yiu Lam
    • 4
  • Shan Feng
    • 5
  1. 1.Bell Labs, Alcatel-LucentMurray HillUSA
  2. 2.Department of Computer SciencesUniversity of Texas at AustinAustinUSA
  3. 3.Emerson Process ManagementAustinUSA
  4. 4.Department of Computer ScienceCity University of Hong KongKowloonHong Kong
  5. 5.The Mathematics and Software Science CollegeSichuan Normal UniversityChengduChina

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