Power-aware resource allocation for independent tasks in heterogeneous real-time systems

Abstract

In recent years, power management and power reduction has become a critical issue in portable systems that are designed for real-time use. In this paper, we study the problem of static allocation of a set of independent tasks onto a real-time system consisting of heterogeneous processing elements, each enabled with discrete Dynamic Voltage Scaling. The allocation problem is first formulated as an extended Generalized Assignment Problem. A linearization heuristic (LR-heuristic) is then extended for solving the problem. An analysis of the upper bound on the number of tasks that the heuristic may fail to allocate is also presented. Our experiments show that when the real-time constraints are tight, the LR-heuristic achieves 15% off the optimal energy consumption for small size problems, while the performance of a classic greedy heuristic is around 90% off the optimal. A relative performance improvement of up-to 40% over the classic greedy heuristic is also observed for large size problems.