Probabilistic adaptive load balancing for parallel queries

In the context of adaptive query processing (AQP), several techniques have been proposed for dynamically adapting/redistributing processor load assignments throughout a computation to take account of varying resource capabilities. The effectiveness of these techniques depends heavily on when and to what they adapt processor load assignments, particularly in the presence of varying load imbalance. This paper presents a probabilistic approach to decide when and to what to adapt processor load assignments. Using a simulation based evaluation, it is compared to two other approaches already reported. These two approaches are simpler in their decision making than the probabilistic approach, but the latter performs better under several scenarios of load imbalance.