Some General Terminal and Network Teletraffic Equations for Virtual Circuit Switching Systems

Poryazov, Stoyan; Saranova, Emiliya

doi:10.1007/0-387-34167-6_24

Cited by 11 publications

(3 citation statements)

References 3 publications

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“…The work presented in this chapter continues the development of the approach for the conceptual and analytical modeling of overall telecommunication systems (with QoS guarantees), presented in [6].…”

Section: Introductionmentioning

confidence: 87%

“…In this chapter, we propose a considerable extension of the conceptual and analytical performance models of the overall telecommunication system with QoS guarantees, described in [6]. This includes two new service branches corresponding to the cases of 'called party being busy with another call' and 'mailing a message'.…”

Section: Conceptual Modelmentioning

confidence: 99%

“…Since 2006 [6] we use up to two qualifiers as a part of the parameter's name. The first is for the parameter value's origin, e.g.…”

Section: Basic Virtual Devices' Name Notationmentioning

confidence: 99%

See 2 more Smart Citations

Conceptual and Analytical Models for Predicting the Quality of Service of Overall Telecommunication Systems

Poryazov¹,

Saranova²,

Ганчев³

2018

Lecture Notes in Computer Science

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This chapter presents scalable conceptual and analytical performance models of overall telecommunication systems, allowing the prediction of multiple Quality of Service (QoS) indicators as functions of the user-and network behavior. Two structures of the conceptual presentation are considered and an analytical method for converting the presentations, along with corresponding additive and multiplicative metrics, is proposed. A corresponding analytical model is elaborated, which allows the prediction of flow-, time-, and traffic characteristics of terminals and users, as well as the overall network performance. In accordance with recommendations of the International Telecommunications Union's Telecommunication Standardization Sector (ITU-T), analytical expressions are proposed for predicting four QoS indicators. Differentiated QoS indicators for each subservice, as well as analytical expressions for their prediction, are proposed. Overall pie characteristics and their causal aggregations are proposed as causal-oriented QoS indicators. The results demonstrate the ability of the model to facilitate a more precise dynamic QoS management as well as to serve as a source for predicting some Quality of Experience (QoE) indicators.

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Section: Introductionmentioning

confidence: 87%

Section: Conceptual Modelmentioning

confidence: 99%