Evaluation and Optimization of the Robustness of DAG Schedules in Heterogeneous Environments

A schedule is said to be robust if it is able to absorb some degree of uncertainty in task or communication durations while maintaining a stable solution. This intuitive notion of robustness has led to a lot of different metrics and almost no heuristics. In this paper, we perform an experimental study of these different metrics and show how they are correlated to each other. Additionally, we propose different strategies for minimizing the makespan while maximizing the robustness: from an evolutionary metaheuristic (best solutions but longer computation time) to more simple heuristics making approximations (medium quality solutions but fast computation time). We compare these different approaches experimentally and show that we are able to find different approximations of the Pareto front for this bicriteria problem.