Cognitive Radio Networks: Analysis of a Paid-Sharing Approach Based on Admission Control Decisions

Rattaro, Claudina; Belzarena, Pablo

doi:10.1007/s11277-018-5805-3

Cited by 3 publications

(1 citation statement)

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“…Furthermore, there is a cost per interrupted customer due to the server's failure. For example, in cognitive radio networks, secondary users (SUs) have to pay to the primary user's (PUs) service provider for spectrum utilization under a paid spectrum sharing mechanism, and the SUs interrupted by arriving PUs will be reimbursed with V , implying a punishment for the service provider; see for instance, Rattaro and Belzarena [24] and Turhan et al [25].…”

Section: Introductionmentioning

confidence: 99%

Optimal Pricing Analysis of Computer Networks Based on a Queueing System With Retrial Mechanism

Zhang

2020

IEEE Access

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We consider a single-server retrial queue with a Poisson arrival process and exponential service times, where the server is unreliable. Assume there is no waiting space in front of the server and the customer who finds the server unavailable joins an orbit to access the server some time later. We discuss two types of customers' retrial behavior. One is that each customer in the orbit seeks for services independently and the total retrial rate of the system depends on the number of customers in the orbit. The other type of retrial discipline is called constant retrial policy and it arises from some situations in the computer and communication network where the retrial rate may be controlled by automatic mechanisms. An announced price charged by the server is imposed on customers joining the system and the actual demands for services depend on the price via a decreasing function. We investigate the system characteristics and study how the manager, whose goal is to maximize its own profit, determines the price charging joining customers. Finally, we present an application example to illustrate the obtained results and make comparisons between the two retrial policies from the perspective of customers' expected waiting time.

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Section: Introductionmentioning

confidence: 99%