On the Application of the Asymmetric Convolution Algorithm in Modeling of Full-Availability Group with Bandwidth Reservation

Głąbowski, Mariusz; Kaliszan, Adam; Stasiak, Maciej

doi:10.1007/978-3-540-72990-7_76

Cited by 11 publications

(12 citation statements)

References 20 publications

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“…In calculations of multiservice systems with traffic overflow, the so-called convolution algorithms [20,22,42,43] can also be used. The advantage of these algorithms is that they offer a possibility to model systems with any streams of offered traffic.…”

Section: Related Workmentioning

confidence: 99%

“…The advantage of these algorithms is that they offer a possibility to model systems with any streams of offered traffic. References [22,42,43] propose convolution models of systems with reservation. In [44], the authors of the paper describe, for the first time, the problem of modelling systems with overflow traffic with the application of the convolution mechanism.…”

Section: Related Workmentioning

confidence: 99%

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Two-Dimensional Convolution Algorithm for Modelling Multiservice Networks with Overflow Traffic

Głąbowski

Kaliszan

Stasiak

2013

Mathematical Problems in Engineering

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The present paper proposes a new method for analytical modelling multiservice networks with implemented traffic overflow mechanisms. The basis for the proposed method is a special two-dimensional convolution algorithm that enables determination of the occupancy distribution and the blocking probability in network systems in which traffic streams of individual classes can be serviced by both primary and alternative resources. The algorithm worked out by the authors makes it possible to model systems with any type of traffic offered to primary resources. In order to estimate the accuracy of the proposed method, the analytical results of blocking probabilities in selected networks with traffic overflow have been compared with simulation data.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Two-Dimensional Convolution Algorithm for Modelling Multiservice Networks with Overflow Traffic

Głąbowski

Kaliszan

Stasiak

2013

Mathematical Problems in Engineering

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“…In this paper, we focus on convolution algorithms which are adopted in the literature not only in the case of loss/queueing models whose steady state probabilities have a product form solution (PFS) but also in the case of non-PFS models (e.g., [8]- [16]). Such algorithms are advantageous not only due to their low computational complexity but also because they can incorporate various resource sharing policies such as the complete sharing policy, the bandwidth reservation policy and threshold-based policies (e.g., [17]- [24]).…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic

Chousainov

Moscholios

Kaloxylos

et al. 2020

J. commun. softw. syst. (Online)

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In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units (BBUs). The RRHs in the C-RAN are grouped in different clusters according to their capacity while the BBUs form a centralized pool of computational resource units. Each RRH services a finite number of mobile users, i.e., the call arrival process is the quasi-random process. A new call of a single service-class requires a radio and a computational resource unit in order to be accepted in the C-RAN for a generally distributed service time. If these resource units are unavailable, then the call is blocked and lost. To analyze the multi-cluster C-RAN, we model it as a single-rate loss system, show that a product form solution exists for the steady state probabilities and propose a convolution algorithm for the accurate determination of congestion probabilities. The accuracy of this algorithm is verified via simulation. The proposed model generalizes our recent model where the RRHs in the C-RAN are grouped in a single cluster and each RRH accommodates quasi-random traffic.

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“…Appropriate convolution algorithms to model full-availability multiservice systems with losses and multiservice access network systems (the so-called multiservice tree network) are proposed in [16][17][18]. Papers [19,20] propose convolution algorithms to model multiservice full-availability systems with resource reservation. Paper [21] develops and discusses a two-dimensional convolution model for a multiservice overflow system.…”

Section: Introductionmentioning

confidence: 99%

Convolution Model of a Queueing System with the cFIFO Service Discipline

Hanczewski

Kaliszan

Stasiak

2016

Mobile Information Systems

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This article presents an approximate convolution model of a multiservice queueing system with the continuous FIFO (cFIFO) service discipline. The model makes it possible to service calls sequentially with variable bit rate, determined by unoccupied (free) resources of the multiservice server. As compared to the FIFO discipline, the cFIFO queue utilizes the resources of a multiservice server more effectively. The assumption in the model is that the queueing system is offered a mixture of independent multiservice Bernoulli-Poisson-Pascal (BPP) call streams. The article also discusses the results of modelling a number of queueing systems to which different, non-Poissonian, call streams are offered. To verify the accuracy of the model, the results of the analytical calculations are compared with the results of simulation experiments for a number of selected queueing systems. The study has confirmed the accuracy of all adopted theoretical assumptions for the proposed analytical model.

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On the Application of the Asymmetric Convolution Algorithm in Modeling of Full-Availability Group with Bandwidth Reservation

Cited by 11 publications

References 20 publications

Two-Dimensional Convolution Algorithm for Modelling Multiservice Networks with Overflow Traffic

Two-Dimensional Convolution Algorithm for Modelling Multiservice Networks with Overflow Traffic

Performance Evaluation in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic

Convolution Model of a Queueing System with the cFIFO Service Discipline

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