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The presented study elaborates a multi-server catastrophic retrial queueing model considering preemptive repeat priority policy with phase-type (PH) distributed retrial times. For the sake of comprehension, the scenario of model operation prior and later to the occurrence of the disaster is referred to as the normal scenario and as the catastrophic scenario, respectively. In the normal scenario, the incoming heterogeneous calls are categorized as handoff calls and new calls. Handoff calls are provided controllable preemptive priority over new calls. In the catastrophic scenario, when a disaster causes the shut down of the entire system and failure of all functioning channels, a set of backup channels is quickly deployed to restore services. Due to the emergency situation in the concerned area, the incoming heterogeneous calls are divided into three categories: handoff, new call, and emergency calls. Emergency calls are provided controllable preemptive priority over new/handoff calls due to the pressing need to save lives in such situations. The Markov chain's ergodicity criteria are established by demonstrating that it belongs to the class of asymptotically quasi-Toeplitz Markov chains (AQTMC). Further, a multi-objective optimization problem to obtain optimal number of backup channels has been formulated and dealt by employing non-dominated sorting genetic algorithm-II (NSGA-II) approach., Comment: arXiv admin note: substantial text overlap with arXiv:2201.08182

The presented study elaborates a multi-server catastrophic retrial queueing model considering preemptive repeat priority policy with phase-type (PH) distributed retrial times. For the sake of comprehension, the scenario of model operation prior and later to the occurrence of the disaster is referred to as the normal scenario and as the catastrophic scenario, respectively. In both scenarios, the arrival and service processes of all types of calls follow marked Markovian arrival process (MMAP) and PH distribution with distinct parameters, respectively. In the normal scenario, the incoming heterogeneous calls are categorized as handoff calls and new calls. An arriving new call will be blocked when all the channels are occupied, and consequently, will join the orbit (virtual space) of infinite capacity. From the orbit, the blocked new call can either retry for the service or exit the system following PH distribution. Whereas, an arriving handoff call is given preemptive repeat priority over a new call in service when all the channels are occupied and at least one of the channel is occupied with a new call otherwise the handoff call is dropped, and consequently, this preempted new call will join the orbit. In the catastrophic scenario, when a disaster causes the shut down of the entire system and failure of all functioning channels, a set of backup channels is quickly deployed to restore services. The Markov chain's ergodicity criteria are established by demonstrating that it belongs to the class of asymptotically quasi-Toeplitz Markov chains (AQTMC). For the approximate computation of the stationary distribution, a new approach is developed. An optimization problem to obtain optimal value of total number of backup channels has been formulated and dealt by employing non dominated sorting genetic algorithm-II (NSGA-II) approach., Comment: arXiv admin note: text overlap with arXiv:2107.07867

The presented study elaborates a multi-server priority queueing model considering the pre-emptive repeat policy and phase-type distribution (PH) for retrial process. The incoming heterogeneous calls are categorized as handoff calls and new calls. The arrival and service processes of both types of calls follow marked Markoian arrival process (MMAP) and PH distribution with distinct parameters, re-spectively. An arriving new call will be blocked when all the channels are occupied, and consequently will join the orbit (virtual space) of infinite capacity to retry following PH distribution. When all the channels are occupied and a handoff call arrives at the system, out of the following two scenarios, one might take place. In the first scenario, if all the channels are occupied with handoff calls, the arriving handoff call will be lost from the system. While in the second one, if all the channels are occupied and at least one of them is serving a new call, the arriving handoff call will be provided service by using preemptive priority over that new call and the preempted new call will join the orbit. Behaviour of the proposed system is modelled by the level dependent quasi-birth-death (LDQBD) process. The expressions of various performance measures have been derived for the numerical illustration. An optimization problem traffic control has been formulated and dealt by employing appropriate heuristic approaches.

This work focuses over the performability analysis of a multi-server retrial queueing model with phase-type inter-retrial times in cellular networks. It is considered that the pattern of the new call arrival and handoff call arrival follows Markovian arrival process (MAP). The service times of both types of calls are phase-type (PH ) distributed with different service rates, and inter-failure & inter-repair times of channels are exponentially distributed. For the prioritization of handoff calls, G channels are kept in reserve for handoff calls. When all the available channels, say S, are busy at the arrival epoch of a handoff call, the handoff call will be dropped. Whereas a new call will be blocked and will have an option to join the orbit of infinite capacity or leave the system without getting the connection, if at least S-G channels are busy. A new call in the orbit, termed as retrial call, retries to get the connection after a random interval which follows PH distribution. This model is analyzed as a level-dependent-quasi-birth-death (LDQBD) process by applying matrix-analytic method (MAM). Further, the closed-form expressions for essential performance measures of the proposed model are derived. Through numerical illustrations, the behaviour of performance measures depending on the various relevant intensities is discussed. An expected cost optimization problem is formulated to determine the optimal value of service intensity and the optimal value of repair intensity. The cost function analysis is executed by employing Simulated Annealing (SA) method.

In this study, we extend upon the model by Haring et al. (2001) by introducing retrial phenomenon in multi-server queueing system. When at most g number of guard channels are available, it allows new calls to join the retrial group. This retrial group is called orbit and can hold a maximum of m retrial calls. The impact of retrial over certain performance measures is numerically investigated. The focus of this work is to construct optimization problems to determine the optimal number of channels, the optimal number of guard channels and the optimal orbit size. Further, it has been emphasized that the proposed model with retrial phenomenon reduces the blocking probability of new calls in the system.