An LMI-neural network based solution to the load balancing problem for heterogeneous local clusters

A solution for the load balancing problem in local clusters of heterogeneous processors is proposed within the setting of delayed artificial neural networks, optimal control and linear matrix inequalities (LMI) theory. Based on a mathematical model that includes delays and processors with different processing velocities, this model is transformed into a special case of delayed cellular neural networks model. A systematic method of controller synthesis is derived, based on two coupled linear matrix inequalities - one guaranteeing global convergence and the other guaranteeing performance in the linear region of operation. Simulations and computational experiments show the efficiency of this approach, reducing load balancing time.