Event-driven semi-Markov switching state-space control processes

Abstract

Motivated by the optimisation of network communication systems, this paper presents a hierarchical analytical model for event-driven switching control of stochastic dynamic systems. First, the model called semi-Markov switching state-space control processes is introduced. The semi-Markov kernel and equivalent infinitesimal generator are constructed to characterise the hierarchical dynamics, and the sensitivity formula for performance difference under average criterion is derived based on potential theory. Then, by exploiting the structure of dynamic hierarchy and the features of event-driven policy, an online adaptive optimisation algorithm that combines potentials estimation and policy iteration is proposed. The convergence of this algorithm is also proved. Finally, as an illustrative example, the dynamic service composition problem in service overlay networks is formulated and addressed. Simulation results demonstrate the effectiveness of the presented approach.