Modelling overflow systems with distributed secondary resources

Głźbowski, Mariusz; Kaliszan, Adam; Stasiak, Maciej

doi:10.1016/j.comnet.2016.08.015

Cited by 34 publications

(24 citation statements)

References 27 publications

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“…The occupancy distribution in SR can be approximated by the distribution proposed in [47] which, in the adopted notation for the distribution (11) for v = (V 0 +V vir 0 )/Z 0 , can be written as follows: (21) Note that if the compression mechanism is applied only in PR (SR), then to model the resources of SR (PR) the model (19) (model (18)) is used.…”

Section: Model Of a System With Streaming Trafficmentioning

confidence: 99%

“…The model [41], [42] has provided a basis for a construction of a large number of advanced models of overflow systems. For example, in [47], [48], limited availability of secondary resources is taken into consideration, while in [49], systems with multiservice Engset traffic streams, generated by a finite number of traffic sources, are considered. A possibility to service elastic traffic is taken into consideration in [47], [50], while in [51] a model of an overflow system with adaptive traffic is developed.…”

Section: Introductionmentioning

confidence: 99%

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Overflows in Multiservice Systems

Głąbowski

Kmiecik

Stasiak

2019

IEICE Trans. Commun.

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This article presents a universal and versatile model of multiservice overflow systems based on Hayward's concept. The model can be used to analyze modern telecommunications and computer networks, mobile networks in particular. The advantage of the proposed approach lies in its ability to analyze overflow systems with elastic and adaptive traffic, systems with distributed resources and systems with non-full-availability in primary and secondary resources.

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Section: Model Of a System With Streaming Trafficmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Overflows in Multiservice Systems

Głąbowski

Kmiecik

Stasiak

2019

IEICE Trans. Commun.

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“…Kaufman-Roberts formula ( [18,28]) has led to various extensions of the EMLM either in wired (e.g., [10,12,13,15,16,19,21,26,31,33,34,36,39]) or wireless (e.g., [5,7,17,22,27,35,37,38,44,47]), satellite (e.g., [45,46]) and optical networks (e.g., [3,4,6,[41][42][43]).…”

Section: Moscholiosmentioning

confidence: 99%

“…In the case of the CS policy, G(j)'s can be determined by the classical Kaufman-Roberts recursion (9), CBP by (10) and the values of y k (j) by (11) ( [18,28]):…”

Section: Moscholiosmentioning

confidence: 99%

Congestion Probabilities in Erlang-Engset Multirate Loss Models under the Multiple Fractional Channel Reservation Policy

Moscholios

2016

Image Processing &Amp; Communications

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A communication link that accommodates different service-classes whose calls have different bandwidth requirements and compete for the available bandwidth under the Multiple Fractional Channel Reservation (MFCR) policy is considered. The MFCR policy allows the reservation of real number of channels in order to favor high speed calls. Two call arrival processes are studied: i) the Poisson (random) process and ii) the quasi-random process. In the first case, calls come from an infinite number of sources while in the second case calls are generated by a finite number of sources. To determine call blocking probabilities for Poisson arriving calls, recursive formulas are proposed based on reverse transition rates. To determine time and call congestion probabilities for quasi-random arriving calls, recursive formulas are proven based on the fact that the steady state probabilities cannot be described by a product form solution. The accuracy of the new formulas is verified through simulation.

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“…The traffic overflow mechanism is applied in optimization of network resources, irrespective of the actual networking technology involved. The possibility to limit the amount of network resources being used offered by the operation of the mechanism, simultaneously with guaranteed demanded quality parameters being retained, has resulted in its wide application in both Public Switched Telephone Networks [2, 5, 25-27, 29, 32], 2G, 3G, and 4G mobile networks [4,9,17,19,20,28,30,31] and packet networks [6,8,10].…”

Section: Introductionmentioning

confidence: 99%

Overflows of Elastic Traffic

Głąbowski

Kmiecik

2017

Image Processing &Amp; Communications

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This article presents the results of a study on hierarchical multiservice traffic overflow systems. The systems under investigation were composed of a number of primary resources and one alternative resource. Traffic in the considered systems was generated with the assumption that there was a finite number of traffic sources in individual classes. Further assumption was that offered traffic is elastic traffic for which – with an increase of the load of the system – a change in the volume of allocated resources is possible followed by concurrent extension of their service time. The article includes the results that present the blocking probability in the sample elastic traffic overflow systems. The study focuses on a determination of the influence of the traffic intensity, volume of resources, degree of compression, resource with compression (primary resources, alternative resources) and the cardinality of traffic sources on values of the blocking probability in individual call classes and on the number of calls that overflow to the alternative resource.

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Modelling overflow systems with distributed secondary resources

Cited by 34 publications

References 27 publications

Overflows in Multiservice Systems

Overflows in Multiservice Systems

Congestion Probabilities in Erlang-Engset Multirate Loss Models under the Multiple Fractional Channel Reservation Policy

Overflows of Elastic Traffic

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