Dynamic Resource Allocation Heuristics for Maximizing Robustness with an Overall Makespan Constraint in an Uncertain Environment

Heterogeneous parallel and distributed computing systems may operate in an environment where certain system performance features degrade due to unpredictable circumstances. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. This work uses a mathematic expression of robustness for a dynamic environment where task execution time estimates are known to contain errors. Several heuristic solutions to the problem are presented that utilize this expression of robustness to influence mapping decisions. These solutions are then compared to a bound on the highest attainable robustness of the described system.