  Stochastic networks with complex structures are key modelling tools for many
important applications. In this paper, we consider a specific type of network:
the retrial queueing systems with priority. This type of queueing system is
important in various applications, including telecommunication and computer
management networks with big data. For this type of system, we propose a
detailed stochastic decomposition approach to study its asymptotic behaviour of
the tail probability of the number of customers in the steady-state for retrial
queues with two types (Type-1 and Type-2) of customers, in which Type-1
customers (in a queue) have non-preemptive priority to receive service over
Type-2 customers (in an orbit). Under the assumption that the service times of
Type-1 customers have a regularly varying tail and the service times of Type-2
customers have a tail lighter than Type-1 customers, we obtain tail asymptotic
properties for the number of customers in the queue and in the orbit,
respectively, conditional on the server's status, in terms of a detailed
stochastic decomposition approach. Tail asymptotic properties are often used as
key tools for approximating various performance metrics and constructing
numerical algorithms for computations.
