CONCLUSIONS

We have successfully demonstrated an automated process for improving the performance of parameterized load-balancing strategies. Our learning system, SMALL, discovers new load indices that can be meaningfully compared across the sites of a configurationally heterogeneous but architecturally homogeneous distributed system.