ILP models for the allocation of recurrent workloads upon heterogeneous multiprocessors

Sanjoy K. Baruah (), Vincenzo Bonifaci (), Renato Bruni () and Alberto Marchetti-Spaccamela ()
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Sanjoy K. Baruah: University of North Carolina at Chapel Hill
Vincenzo Bonifaci: CNR
Renato Bruni: Università di Roma “Sapienza”
Alberto Marchetti-Spaccamela: Università di Roma “Sapienza”

Journal of Scheduling, 2019, vol. 22, issue 2, No 6, 195-209

Abstract: 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.

Keywords: Task partitioning; Sporadic tasks; Unrelated machines; Speedup bound; ILP rounding (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10951-018-0593-x

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