Abstract

The problem of partitioning systems of independent constrained-deadline sporadic tasks upon heterogeneous multiprocessor platforms is considered. Several different integer linear program (ILP) formulations of this problem, offering different trade-offs between effectiveness (as quantified by speedup bound) and running time efficiency, are presented. One of the formulations is leveraged to improve the best speedup guarantee known for a polynomial-time partitioning algorithm, from 12.9 to 7.83. Extensive computational results on synthetically generated instances are also provided to establish the effectiveness of the ILP formulations.

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