Markov model of controlled load distribution in the edge-IoT subsystem

Abstract

The article presents a hybrid Markov model of adaptive load distribution within edge-IoT subsystems operating under conditions of stochastic traffic and heterogeneous environments. The proposed approach formalises the set of admissible and critical system states and introduces a routing policy with a probabilistic guarantee of stabilisation within QoS-defined configurations. For the first time, an integral efficiency criterion is proposed, combining the probability of remaining in desirable states with the minimum probability of stabilisation under perturbations. The model enables the development of adaptive routing strategies that minimise servicing costs and enhance resilience against node degradation and traffic fluctuations. Experimental results demonstrate the superiority of the proposed approach over classical strategies (round-robin and random) in terms of average delay, resource utilisation, and the loss function. The model has practical relevance for 6G edge architectures, autonomous systems, eHealth, and critical IoT infrastructures.