Performance Analysis and Optimization of Multi-Traffic on Communication Networks

Пономаренко, Л. А.; Kim, Che Soong; Melikov, Agassi

doi:10.1007/978-3-642-15458-4

Cited by 43 publications

(30 citation statements)

References 7 publications

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“…As the dimension of PSS (2) grows, this method can experience some computing difficulties. To eliminate them, it is possible to use the method of approximate calculation of the stationary distribution of two-dimensional Markov chains (see Appendix in [7]). …”

Section: (4)mentioning

confidence: 99%

Numerical Analysis of a Queueing System with Feedback

2015

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A mathematical model of the multichannel queueing system with feedback is proposed. The feedback occurs as returning a part of serviced calls to get a new service. The probability of returning to orbit depends on the number of busy channels. Both models with finite and infinite orbits are examined. Both exact and approximate methods to calculate characteristics of the system are developed. The results of numerical experiments are given.

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Section: (4)mentioning

confidence: 99%

Numerical Analysis of a Queueing System with Feedback

2015

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“…As we could realize queueing theory can be successfully applied to establish mathematical models for variety of telecommunication systems (see e.g. [1], [2], [3], [6], [7], [8], [11], [12], [16], [17], [18], ). These models can be used to calculate performance measures like mean delay, mean waiting time, utilization of the frequency bands etc.…”

Section: Introductionmentioning

confidence: 99%

Performance Modeling of Finite-Source Cognitive Radio Networks

et al. 2016

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This paper deals with performance modeling aspects of radio frequency licensing. The utilization of mobile cellular networks can be increased by the idea of the cognitive radio. Licensed users (Primary Users -PUs) and normal users (Secondary Users -SUs) are considered. The main idea is, that the SUs are able to access to the available non-licensed radio frequencies. A finite-source retrial queueing model with two non independent frequency bands (considered as service units) is proposed for the performance evaluation of the system. A service unit with a priority queue and another service unit with an orbit are assigned to the PUs and SUs, respectively. The users are classified into two classes: the PUs have got a licensed frequency, while the SUs have got a frequency band, too but it suffers from the overloading. We assume that during the service of the non-overloaded band the PUs have preemptive priority over SUs. The involved inter-event times are supposed to be independent and exponentially distributed random variables. The novelty of this work lies in the fact that we consider the effect of retrial phenomenon of SUs in performance modeling of radio frequency licensing by using a finite-source queueing model which takes the unreliability of radio transmission into account for the first time. In the literature, most work studied the performance of cognitive radio networks under a mixed spectrum environment of licensed and unlicensed bands where the blocked SUs and the preempted SUs are forced to leave the system forever when there are no idle channels in the system. But in practical situation, the blocked SUs and the preempted SUs may do not leave the system forever and try to continue their services after random amount of time. By the help of an appropriate continuous time Markov chain using MOSEL (MOdeling Specification and Evaluation Language) tool several numerical examples are provided showing the effects of different input parameters on the main performance measures of the cognitive radio networks. Our primary focus is to determine an optimal number of SUs, where at the * University of Debrecen, Hungary, E-mail: almasi.bela,berczes.tamas, kuki.attila, sztrik.janos@inf.unideb.hu † Beijing Jiaotong University, China E-mail: jtwang@bjtu.cn DOI: 10.14232/actacyb.22.3.2016.5 618 B. Almási, T. Bérczes, A. Kuki, J. Sztrik, J. Wang secondary band the gained utilization, that is when switching to the cognitive radio, has a maximum value.

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“…The proposed method is based on the fundamental ideas of the theory of phase merging of stochastic systems [21]. Furthermore its counterpart for the 2-D MC was successfully used in the study of various models of single-phase queueing systems [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Space Merging Algorithm for Analysis of Two Stage Queueing Network with Feedback

Melikov¹,

Пономаренко

Rustamov

et al. 2016

Communications in Computer and Information Science

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Abstract. A Markov model of two stage queuing network with feedback is proposed. Poisson flows arriving to both stages from outside and part of already serviced calls in the first node instantaneously enter to the second node (if there is free space here) while the remaining part leaves the network. At the completion of call processing in the second node there are three possibilities: (1) it leaves the network; (2) it instantaneously feeds back to the first node (if there is free space here); (3) it feeds back to the first node after some delay in orbit. All feedbacks are determined by known probabilities. Both nodes have finite capacities. The mathematical model of the investigated network is a three dimensional Markov chain (3-D MC) and hierarchical space merging algorithm to calculate its steady-state probabilities is developed. This algorithm allows asymptotic analysis of the quality of service (QoS) metrics of the investigated network as well.

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Performance Analysis and Optimization of Multi-Traffic on Communication Networks

Abstract: The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

Cited by 43 publications

References 7 publications

Numerical Analysis of a Queueing System with Feedback

Numerical Analysis of a Queueing System with Feedback

Performance Modeling of Finite-Source Cognitive Radio Networks

Hierarchical Space Merging Algorithm for Analysis of Two Stage Queueing Network with Feedback

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