Hybrid optimal control for load balancing in a cluster of computer nodes

This paper develops a hybrid optimal control technique and resulting experimental data using a previously reported deterministic dynamic nonlinear system model for load balancing in a cluster of computer nodes used for parallel computations in the presence of time delays and resource constraints. The model accounts for the trade-off between using processor resources to process tasks and transferring tasks to distribute the load evenly between the nodes to reduce overall processing time. The desired performance is achieved using hybrid optimal control techniques in a model predictive control context. Results demonstrate superior performance.