Online Load Balancing in Parallel Database Queries With Model Predictive Control
In this paper the authors deal with a commonly encountered instantiation of the more generic problem of runtime load balancing. More specifically, they study load balancing in the context of query plans that include partitioned database operators running on remote nodes with time-varying connection speeds and loads. In such query plans, data is processed by similar operator instances placed on different machines in parallel, e.g., using a cloud infrastructure. The goal is to adaptively distribute the data to respond to changes in the environment, in such a way that all machines finish at the same time.