A load balancing task allocation scheme in a hard real time system

  • Jean Louis Lanet
Workshop 17 Scheduling and Load Balancing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1124)


We address the problem of allocating real-time tasks subject to precedence constraints in a distributed system. The use of a list algorithm is a good trade-off between the complexity of the algorithm and the quality of the solution. The optimisation criterion is the load balancing which is linked with the fault tolerance requirements. Such a criterion guarantees that every processor will spend the same amount of time in performing self tests. The application is described by an acyclic graph giving the precedence constraints. To ensure that no deadline will be missed we have to build and check the whole sequence. Allocating and scheduling are handled together in a static approach.


Distributed System Real Time Load Balancing List Scheduling 


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  1. [1]
    LANET, Placement statique de tâches dans un calculateur réparti de régulation moteur. Thesis, University of Paris 6, 1995.Google Scholar
  2. [2]
    LANET, Task Allocation in a Hard Real Time Distributed System. Real Time Systems'95, pp. 244–252, Sklarska Poreba, Poland, Sept.-95.Google Scholar
  3. [3]
    LU, CAREY, Load Balanced Task Allocation in Locally Distributed Computer Systems. Computer Science Technical Report #633, University of Wisconsin, Madison, Feb.-86.Google Scholar
  4. [4]
    RAMAMRITHAM, Allocation and Scheduling of Complex Periodic Tasks. IEEE 10th International Conference on Distributed Computing Systems, Jan.-90, pp. 108–115.Google Scholar
  5. [5]
    TINDELL, BURNS, WELLINGS, Allocating Hard Real Time Tasks: an NP-Hard Problem Made Easy. The Journal of Real Time Systems, Nℴ4, 1992, pp. 145–165.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Jean Louis Lanet
    • 1

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