scholarly journals Stochastic analysis of a single server unreliable queue with balking and general retrial time

2020 ◽  
Vol 28 (4) ◽  
pp. 319-326
Author(s):  
Mohamed Boualem
Keyword(s):  
Markov Chain ◽  
Cognitive Radio ◽  
Stochastic Analysis ◽  
Manufacturing Systems ◽  
Cognitive Radio Network ◽  
Stochastic Orders ◽  
Embedded Markov Chain ◽  
Single Server ◽  
Radio Network ◽  
If Current

In this investigation, we consider an M/G/1 queue with general retrial times allowing balking and server subject to breakdowns and repairs. In addition, the customer whose service is interrupted can stay at the server waiting for repair or leave and return while the server is being repaired. The server is not allowed to begin service on other customers until the current customer has completed service, even if current customer is temporarily absent. This model has a potential application in various fields, such as in the cognitive radio network and the manufacturing systems, etc. The methodology is strongly based on the general theory of stochastic orders. Particularly, we derive insensitive bounds for the stationary distribution of the embedded Markov chain of the considered system.

Computation of Performance Parameters in Multi-service Cognitive Radio Networks

2013 ◽  
pp. 234-247
Author(s):  
Hongbing Lian ◽  
Andras Farago
Keyword(s):  
Markov Chain ◽  
Cognitive Radio ◽  
Cognitive Radio Network ◽  
Blocking Probability ◽  
Radio Network ◽  
Performance Parameters ◽  
Stationary Distributions ◽  
Call Dropping ◽  
The Status ◽  
Qos Performance

In this chapter the authors consider a cognitive cellular network that allows secondary (cognitive) users to access the bandwidth that is left over by the primary users. Furthermore, the authors allow multiple traffic classes in the system. The analysis of such a network is complicated by the fact that the secondary users face a randomly changing available capacity to serve their demands. The authors start with the multi-class Call Admission Control (CAC) model for existing Primary Radio Network (PRN). Then the authors propose a multi-class CAC model for Cognitive Radio Network (CRN) with different call blocking and call dropping thresholds for different class of services. The authors build up their analytical models for PRN and CRN based on Markov chain. The PRN works as if there is no interference from CRN. But the CRN needs to sense the status of PRN and to utilize the unused channels left by PRN. So the CRN is dependent on the PRN traffic load. The authors use a multi- dimensional Markov chain to model the CRN status under the condition of certain channels unused by the PRN. The authors can get the stationary distributions over all possible states of PRN and CRN. The Quality of Service (QoS) performance parameters for CRN, such as blocking probability, call dropping probability, and channel utilization can be derived from the obtained stationary distributions. Using it, the authors calculate the QoS performance parameters for multi-service cognitive radio network.

An Energy-Efficient Model of Random Cognitive Radio Network: Rayleigh-Lognormal Environment

2020 ◽  
Vol 114 (3) ◽  
pp. 1963-1981
Author(s):  
Saifur Rahman Sabuj ◽  
Tabassum E Nur ◽  
Masanori Hamamura
Keyword(s):  
Cognitive Radio ◽  
Energy Efficient ◽  
Cognitive Radio Network ◽  
Radio Network
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