A Lower-Bound Algorithm for Load Balancing in Real-Time Systems

  • Cecilia Ekelin
  • Jan Jonsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3144)


We study the problem of finding a safe and tight lower-bound on the load-balancing objective often found in real-time systems. Our approach involves the formulation of the Multiple Bounded Change-Making Problem which we efficiently solve by using a new symmetry-breaking algorithm. An experimental evaluation shows that the computed lower-bound is optimal in more than 70% of the cases and is able to find more than four times as many decidedly optimal solutions.


Schedule Problem Load Balance Knapsack Problem Task Assignment Constraint Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bosi, F., Milano, M.: Enhancing clp branch and bound techniques for scheduling problems. Software-Practice and Experience 31(1), 17–42 (2001)zbMATHCrossRefGoogle Scholar
  2. 2.
    Carlsson, M., Ottosson, G., Carlson, B.: An open-ended finite domain constraint solver. In: Hartel, P.H., Kuchen, H. (eds.) PLILP 1997. LNCS, vol. 1292, pp. 191–206. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  3. 3.
    Chao, H.-Y., Harper, M.P.: A tighter lower bound for optimal bin packing. Operations Research Letters 18, 133–138 (1995)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Chen, G.-H., Yur, J.-S.: A branch-and-bound-with-underestimates algorithm for the task assignment problem with precedence constraint. In: Proc. of the IEEE Int’l Conf. on Distributed Computing Systems, Paris, France, May 28-June 1, pp. 494–501 (1990)Google Scholar
  5. 5.
    Chu, W.W., Lan, L.M.-T.: Task allocation and precedence relations for distributed real-time systems. IEEE Trans. on Computers 36(6), 667–679 (1987)CrossRefGoogle Scholar
  6. 6.
    Ekelin, C., Jonsson, J.: A CLP framework for allocation and scheduling in embedded real-time systems. Tech. Rep. 01-12, Dept. of Computer Engineering, Chalmers University of Technology, S-412 96 Göteborg, Sweden (2001)Google Scholar
  7. 7.
    Ekelin, C., Jonsson, J.: Evaluation of search heuristics for embedded system scheduling problems. In: Proc. of the Int’l Conference on Principles and Practice of Constraint Programming, Paphos, Cyprus, November 26-December 1, pp. 640–654 (2001)Google Scholar
  8. 8.
    Ekelin, C., Jonsson, J.: A lower-bound algorithm for minimizing network communication in real-time systems. In: Proc. of the Int’l Conference on Parallel Processing, Vancouver, Canada, August 18-21, pp. 343–351 (2002)Google Scholar
  9. 9.
    Frisch, A., Hnich, B., Kiziltan, Z., Miguel, I., Walsh, T.: Global constraints for lexicographic orderings. In: Proc. of the Int’l Conference on Principles and Practice of Constraint Programming, Ithaca, New York, September 2002, pp. 93–108 (2002)Google Scholar
  10. 10.
    Johnson, D.S.: Near-Optimal Bin-Packing Algorithms. Ph.D. thesis, Massachusetts Institute of Technology (1974)Google Scholar
  11. 11.
    Korf, R.E.: A new algorithm for optimal bin packing. In: Proc. of the National Conference on Artificial Intelligence, Edmonton, Canada, July 2002, pp. 731–736 (2002)Google Scholar
  12. 12.
    Kulanoot, A.: Algorithms for Some Hard Knapsack Problems. Ph.D. Thesis, School of Mathematics and Statistics, Curtin University of Technology, Perth, Australia (January 2000)Google Scholar
  13. 13.
    Intelligent Systems Laboratory. SICStus Prolog User’s Manual. Swedish Institute of Computer Science (1995) Google Scholar
  14. 14.
    Martello, S., Toth, P.: Knapsack Problems: Algorithms and Computer Implementations. Wiley, Chichester (1990)zbMATHGoogle Scholar
  15. 15.
    Milano, M., van Hoeve, W.J.: Reduced cost-based ranking for generating promising subproblems. In: Proc. of the Int’l Conference on Principles and Practice of Constraint Programming, Ithaca, New York, September 2002, pp. 1–16 (2002)Google Scholar
  16. 16.
    Wu, S.S., Sweeting, D.: Heuristic algorithms for task assignment and scheduling in a processor network. Parallel Computing 20(1), 1–14 (1994)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Cecilia Ekelin
    • 1
  • Jan Jonsson
    • 1
  1. 1.Department of Computer EngineeringChalmers University of TechnologyGöteborgSweden

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