Advertisement

Algorithmica

, Volume 57, Issue 1, pp 44–61 | Cite as

Transactional Contention Management as a Non-Clairvoyant Scheduling Problem

  • Hagit Attiya
  • Leah Epstein
  • Hadas Shachnai
  • Tami Tamir
Article

Abstract

The transactional approach to contention management guarantees consistency by making sure that whenever two transactions have a conflict on a resource, only one of them proceeds. A major challenge in implementing this approach lies in guaranteeing progress, since transactions are often restarted.

Inspired by the paradigm of non-clairvoyant job scheduling, we analyze the performance of a contention manager by comparison with an optimal, clairvoyant contention manager that knows the list of resource accesses that will be performed by each transaction, as well as its release time and duration. The realistic, non-clairvoyant contention manager is evaluated by the competitive ratio between the last completion time (makespan) it provides and the makespan provided by an optimal contention manager.

Assuming that the amount of exclusive accesses to the resources is non-negligible, we present a simple proof that every work conserving contention manager guaranteeing the pending commit property achieves an O(s) competitive ratio, where s is the number of resources. This bound holds for the Greedy contention manager studied by Guerraoui et al. (Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 258–264, 2005) and is a significant improvement over the O(s 2) bound they prove for the competitive ratio of Greedy. We show that this bound is tight for any deterministic contention manager, and under certain assumptions about the transactions, also for randomized contention managers.

When transactions may fail, we show that a simple adaptation of Greedy has a competitive ratio of at most O(ks), assuming that a transaction may fail at most k times. If a transaction can modify its resource requirements when re-invoked, then any deterministic algorithm has a competitive ratio Ω(ks). For the case of unit length jobs, we give (almost) matching lower and upper bounds.

Keywords

Scheduling Transactions Software transactional memory Concurrency control Contention management 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Borodin, A., El-Yaniv, R.: Online Computation and Competitive Analysis. Cambridge University Press, Cambridge (1998) zbMATHGoogle Scholar
  2. 2.
    Edmonds, J., Chinn, D.D., Brecht, T., Deng, X.: Non-clairvoyant multiprocessor scheduling of jobs with changing execution characteristics. J. Sched. 6(3), 231–250 (2003) zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Guerraoui, R., Herlihy, M., Pochon, B.: Toward a theory of transactional contention management. In: Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 258–264 (2005) Google Scholar
  4. 4.
    Guerraoui, R., Herlihy, M., Kapałka, M., Pochon, B.: Robust contention management in software transactional memory. In: Synchronization and Concurrency in Object-Oriented Languages (SCOOL). Workshop, in Conjunction with OOPSLA (2005). http://urresearch.rochester.edu/handle/1802/2103
  5. 5.
    Herlihy, M., Luchangco, V., Moir, M., Scherer III, W.N.: Software transactional memory for dynamic-sized data structures. In: Proceedings of the 22nd Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 92–101 (2003) Google Scholar
  6. 6.
    Irani, S., Leung, V.: Scheduling with conflicts, and applications to traffic signal control. In: Proceedings of the 7th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 85–94 (1996) Google Scholar
  7. 7.
    Kalyanasundaram, B., Pruhs, K.R.: Fault-tolerant scheduling. SIAM J. Comput. 34(3), 697–719 (2005) zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Motwani, R., Phillips, S., Torng, E.: Non-clairvoyant scheduling. Theor. Comput. Sci. 130(1), 17–47 (1994) zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Rosenkrantz, D.J., Stearns, R.E., Lewis II, P.M.: System level concurrency control for distributed database systems. ACM Trans. Database Syst. 3(2), 178–198 (1978) CrossRefGoogle Scholar
  10. 10.
    Scherer III, W.N., Scott, M.: Contention management in dynamic software transactional memory. In: PODC Workshop on Concurrency and Synchronization in Java Programs, pp. 70–79 (2004) Google Scholar
  11. 11.
    Scherer III, W.N., Scott, M.: Advanced contention management for dynamic software transactional memory. In: Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 240–248 (2005) Google Scholar
  12. 12.
    Silberschatz, A., Galvin, P.: Operating Systems Concepts, 5th edn. Wiley, New York (1999) Google Scholar
  13. 13.
    Vossen, G., Weikum, G.: Transactional Information Systems. Morgan Kaufmann, San Mateo (2001) Google Scholar
  14. 14.
    Yao, A.C.C.: Probabilistic computations: towards a unified measure of complexity. In: Proc. 18th Symp. Foundations of Computer Science (FOCS), pp. 222–227. IEEE (1977) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Hagit Attiya
    • 1
  • Leah Epstein
    • 2
  • Hadas Shachnai
    • 1
  • Tami Tamir
    • 3
  1. 1.Computer Science DepartmentThe TechnionHaifaIsrael
  2. 2.Department of MathematicsUniversity of HaifaHaifaIsrael
  3. 3.School of Computer ScienceThe Interdisciplinary CenterHerzliyaIsrael

Personalised recommendations