Applying MGAP Modeling to the Hard Real-time Task Allocation on Multiple Heterogeneous Processors Problem

The usage of heterogeneous multicore platforms is appealing for applications, e.g. hard real-time systems, due to the potential reduced energy consumption offered by such platforms. However, the power wall is still a barrier to improving the processor design process due to the power consumption of components. Hard real-time systems are part of life critical environments and reducing the energy consumption on such systems is an onerous and complex process. This paper reassesses the problem of finding assignments of hard real-time tasks among heterogeneous processors taking into account timing constraints and targeting low power consumption. We also propose models based on a well-established literature formulation of the Multilevel Generalized Assignment Problem (MGAP). We tackle the problem from the perspective of different integer programming mathematical formulations and their interplay on the search for optimal solutions. Experimentation shows that using strict schedulability tests as constraints of 0/1 integer linear programming results in faster solvers capable of finding optimum solutions with lower power consumption.