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

Abstract

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.

Modeling a Linux Packet-Capturing System with a Queueing System with Vacations

“…There is a considerable amount of work that models telecommunications networks by using queueing theory, ranging from the very old to the very new systems [11]. Among those published in recent years, we can mention [12], in which an analytical model was elaborated upon to predict some traffic characteristics, quality of service (QoS) indicators, and the overall network performance. In [13] it is proposed a conceptual model of overall telecommunication system with a queueing system; this analytical model was used to solve aspects such as dimensioning of the network and predicting the QoS.…”

Sensitivity Study of a Large-Scale Air Pollution Model by Using Optimized Stochastic Algorithm

“…The Unified Danish Eulerian Model (UNI-DEM) [14], [15] is used in this particular study. Different parts of the large amount of output data, produced by the model, were used in various practical applications, where the reliability of this data should be properly estimated [11], [13]. Another reason to choose this model as a case study here is its sophisticated chemical scheme, where all relevant chemical processes in the atmosphere are accurately represented.…”