Adaptive load control of the central processor in a distributed system with a star topology

We study adaptive control techniques for controlling the flow of work from the Peripheral Processors (PPs) to the Central Processor (CP) of a distributed system with a star topology. We consider two classes of mechanisms for controlling the flow of jobs from the PPs to the CP: (i) Proportional control: a certain proportion of the load offered by each PP is admitted, and (ii) Threshold control: there is a maximum rate at which jobs from any PP can be admitted. The problem is to obtain good algorithms for dynamically adjusting the control level, in order to meet certain CP performance objectives, when the load offered by the PPs is unknown and varying. We formulate the problem approximately as a standard system control problem in which the system has unknown parameters that are subject to change. Using the naive-feedback-controller and stochastic approximation techniques, we derive adaptive controls for the system control problem. We demonstrate the efficacy of these controls in the original problem by simulations of a queuing model of the CP and the load controls.