Performance evaluation of finite-source cognitive radio networks with non-reliable services using simulation

Nemouchi, Hamza; Sztrik, János

doi:10.33039/ami.2018.12.001

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…In papers [8,12] authors took into consideration that the servers are subject to breakdowns. In these works all the inter-event times including the failure and repair times were exponentially distributed.…”

Section: System Modelmentioning

confidence: 99%

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Simulation of the performance of CognitiveRadio Networks with unreliable servers

Zaghouani¹,

Sztrik²,

Uka³

2020

AMI

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This paper deals with a Cognitive Radio Network (CRN) which is modeled using a retrial queuing system with two finite-sources. This network includes two non-independent service units treating two types of users: Primary Users (PU) and Secondary Users (SU). The primary unit has priority queue (FIFO) and a second service unit contains an orbit both units are dedicated for the Primary Users and Secondary Users, respectively.The current work highlights the unreliability of the servers as we are assuming that both servers of this network are subject to random breakdowns and repairs. All the inter-event times in this CRN are either exponentially or non-exponentially distributed. The novelty of our investigation is to analyze the effect of several distributions (Gamma, Pareto, Log-normal, Hypo-Exponential and Hyper-Exponential) of the failure and repair times on the main performance measure of the system. By the help of simulation we show some interesting results concerning to sensitivity problems.

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Section: System Modelmentioning

confidence: 99%

“…In these works all the inter-event times including the failure and repair times were exponentially distributed. Same authors of papers [8,12] have investigated further the CRN with breakdowns, in paper [9] the failure and repair time of the servers are non-exponential distributed (Hypo-exponentially and Hyperexponentially).…”

Section: System Modelmentioning

confidence: 99%

Simulation of the performance of CognitiveRadio Networks with unreliable servers

Zaghouani¹,

Sztrik²,

Uka³

2020

AMI

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“…The main objective of the CRN is to use the unused portions of the primary frequency bands for the benefit of unlicensed customers. Further details can be found in [1,4,6,[9][10][11][12]17]. Several studies and researches, such as [18,20] show that often many parts of the channels are unused in time and space by licensed users (white spaces).…”

Section: Introductionmentioning

confidence: 99%

Simulation Analysis in Cognitive Radio Networks with Unreliability and Abandonment

Nemouchi

Zaghouani

Sztrik

2021

Information Technologies and Mathematical Modelling. Queueing Theory and Applications

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The current paper presents a Cognitive Radio Network with impatient customers and unreliable servers by the help of a finite-source retrial queueing system. We consider two types of customers (primary and secondary) assigned to two interconnected frequency bands. A first frequency band with a priority queue and a second frequency band with an orbit are reserved for Primary Users (PUs) and Secondary Users (SUs), respectively. If the servers are busy, both customers (licensed and unlicensed) enter either the queue or orbit. Before they enter orbit, the secondary customers receive a random retrial time according to the exponential distribution, i.e. the waiting time before the next retry. Unlicensed users (impatient) are obliged to leave the system as soon as their total waiting time exceeds a random maximum waiting time. It should be noted, that the secondary service unit of our system is subject to random breakdowns and repairs. The novelty of this work consists in the investigation of the abandonment and secondary server unreliability impact on various performance measures of the system (Cognitive Radio Network), such as the mean response and waiting time of users, the probability of abandonment of SU, etc. Several figures illustrate the problem in question through simulation.

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“…In papers [15] and [16] authors used as well Hypo, Hyper and Exponential distributions supposing that the secondary users of the system are subject to collisions and the two services in the system are unreliable, respectively.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

Zaghouani¹,

Sztrik²

2020

AMI

Self Cite

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The current paper takes into consideration a cognitive radio network with impatient customers, by the help of finite-source retrial queueing system. We consider two different types of customers (Primary and Secondary) assigned to two interconnected frequency bands. A first frequency band with a priority queue and a second one with an orbit, both are respectively dedicated for the Primary Users (PUs) and Secondary Users (SUs). In case the servers are busy, both customers (Licensed and Unlicensed) join either the queue or the orbit. Before joining the orbit, secondary customers receive a random retrial time according to Exponential distribution, which is the holding time before the next retry. Unlicensed users (impatient) are obliged to leave the system once their total waiting time exceeds a given maximum waiting time.The novelty of this work is the investigation of the abandonment and its impact on several performance measures of the system such as the mean response time and waiting time of users, probability of abandonment of SU, etc. Several figures illustrate the problem in question by the help of simulation.

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Performance evaluation of finite-source cognitive radio networks with non-reliable services using simulation

Cited by 4 publications

References 10 publications

Simulation of the performance of CognitiveRadio Networks with unreliable servers

Simulation of the performance of CognitiveRadio Networks with unreliable servers

Simulation Analysis in Cognitive Radio Networks with Unreliability and Abandonment

Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

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