Performance modeling of finite-source cognitive radio networks with reverse balking and reneging using simulation

Understanding the impatient behaviour of users and customers has a critical importance for every organization to remain at the forefront in today’s competitive business world. Customers’ most prevalent impatient behaviours are balking and reneging. Customers are discouraged about receiving service when they notice large queues ahead (balking); they may even exit the system after joining if their wait time exceeds expectations (reneging). Nevertheless, in the investment-related industry, the opposite of balking is true, the desire to join a business is great if the number of customers is high, as this can be a very attractive factor for new investors. If the number of existing clients is large, the possibility of connecting to such a business is significant. Thus, the more crowded the system, the more joiners and vice versa (reverse balking).In this article, we study the concepts of reneging and reverse balking in the context of a Cognitive Radio Network. The more crowded our network is, the more likely new calls join, and vice versa. These calls, may also get irritated and abandon the whole system as a result of a lengthy delay. The system’s key performance measures are visually illustrated and acquired using simulation.