Telecommunication traffic: global disparities and international flows

New information and communication technologies (ICTs) have shrunk geographical space and time more than ever. But do people fully use the opportunities provided by the newest ICTs? How intensively do they communicate with each other on the international level? And what are the global disparities in the level of telecommunicativeness and international communicative openness? To answer these questions a study of global telecommunication traffic and the specificity of its spatial organisation has been undertaken based on the official statistics on different types of ICT traffic (postal service, fixed telephone, mobile phone and the Internet) over the last two decades. Indicators in the sphere of telecommunicativeness and international communicative openness are presented. This study expands the understanding of international integration and globalisation processes in their communication aspects

A quantitative analysis of inter-island telephony traffic in the Pacific Basin Region (PBR)

As part of NASA's continuing assessment of future communication satellite requirements, a study was conducted to quantitatively scope current and future telecommunication traffic demand in the South Pacific Archipelagos. This demand was then converted to equivalent satellite transponder capacities. Only inter-island telephony traffic for the Pacific Basin Region was included. The results show that if all this traffic were carried by a satellite system, one-third of a satellite transponder would be needed to satisfy the base-year (1976-1977) requirement and about two-thirds of a satellite transponder would be needed to satisfy the forecasted 1985 requirement

On the accuracy of some polynomial approximations for the kolmogorov–wiener filter weight function

The problem of telecommunication traffic prediction is important for telecommunications and cyber security, see [1]. In paper [2] telecommunication traffic is described as a continuous stationary random process with a power-law structure function. In the framework of this model in papers [3–6] we proposed to use the Kolmogorov–Wiener filter for telecommunication traffic prediction. An approximate solution of the corresponding integral equation for the unknown weight function was obtained on the basis of the truncated polynomial expansion method

Numerical Methods of Multifractal Analysis in Information Communication Systems and Networks

In this chapter, the main principles of the theory of fractals and multifractals are stated. A singularity spectrum is introduced for the random telecommunication traffic, concepts of fractal dimensions and scaling functions, and methods used in their determination by means of Wavelet Transform Modulus Maxima (WTMM) are proposed. Algorithm development methods for estimating multifractal spectrum are presented. A method based on multifractal data analysis at network layer level by means of WTMM is proposed for the detection of traffic anomalies in computer and telecommunication networks. The chapter also introduces WTMM as the informative indicator to exploit the distinction of fractal dimen- sions on various parts of a given dataset. A novel approach based on the use of multifractal spectrum parameters is proposed for estimating queuing performance for the generalized multifractal traffic on the input of a buffering device. It is shown that the multifractal character of traffic has significant impact on queuing performance characteristics

Intelligent Municipal Heritage Management Service in a Smart City: Telecommunication Traffic Characterizationand Quality of Service

[EN] The monitoring of cultural heritage is becoming common in cities to provide heritage preservation and prevent vandalism. Using sensors and video cameras for this task implies the need to transmit information. In this paper, the teletraffic that cameras and sensors generate is characterized and the transmissions¿ influence on the municipal communications network is evaluated. Then, we propose models for telecommunication traffic sources in an intelligent municipal heritage management service inside a smart sustainable city. The sources were simulated in a smart city scenario to find the proper quality of service (QoS) parameters for the communication network, using Valencia City as background. Specific sensors for intelligent municipal heritage management were selected and four telecommunication traffic sources were modelled according to real-life requirements and sensors datasheet. Different simulations were performed to find the proper CIR (Committed Information Rate) and PIR (Peak Information Rate) values and to study the effects of limited bandwidth networks. Packet loss, throughput, delay, and jitter were used to evaluate the network¿s performance. Consequently, the result was the selection of the minimum values for PIR and CIR that ensured QoS and thus optimized the traffic telecommunication costs associated with an intelligent municipal heritage management service.This work was partially supported by Spanish Government Projects TIN2013-47272-C2-1-R and TEC2015-71932-REDTRodríguez-Hernández, MA.; Jiang, Z.; Gomez-Sacristan, Á.; Pla, V. (2019). Intelligent Municipal Heritage Management Service in a Smart City: Telecommunication Traffic Characterizationand Quality of Service. Wireless Communications and Mobile Computing (Online). 1-10. https://doi.org/10.1155/2019/8412542S11

Two Alternative Macro-Based Approaches to Model Telecommunication Traffic

(no abstract available)Series: Discussion Papers of the Institute for Economic Geography and GIScienc

A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction data

Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation. The specification of a problem adequate network topology is a key issue and the primary focus of this contribution. Up to now, this issue has been either completely neglected in spatial application domains, or tackled by search heuristics (see Fischer and Gopal 1994). With the view of modelling interactions over geographic space, this paper considers this problem as a global optimization problem and proposes a novel approach that embeds backpropagation learning into the evolutionary paradigm of genetic algorithms. This is accomplished by interweaving a genetic search for finding an optimal CNN topology with gradient-based backpropagation learning for determining the network parameters. Thus, the model builder will be relieved of the burden of identifying appropriate CNN-topologies that will allow a problem to be solved with simple, but powerful learning mechanisms, such as backpropagation of gradient descent errors. The approach has been applied to the family of three inputs, single hidden layer, single output feedforward CNN models using interregional telecommunication traffic data for Austria, to illustrate its performance and to evaluate its robustness.

Neural Network Modelling of Constrained Spatial Interaction Flows

Fundamental to regional science is the subject of spatial interaction. GeoComputation - a new research paradigm that represents the convergence of the disciplines of computer science, geographic information science, mathematics and statistics - has brought many scholars back to spatial interaction modeling. Neural spatial interaction modeling represents a clear break with traditional methods used for explicating spatial interaction. Neural spatial interaction models are termed neural in the sense that they are based on neurocomputing. They are clearly related to conventional unconstrained spatial interaction models of the gravity type, and under commonly met conditions they can be understood as a special class of general feedforward neural network models with a single hidden layer and sigmoidal transfer functions (Fischer 1998). These models have been used to model journey-to-work flows and telecommunications traffic (Fischer and Gopal 1994, Openshaw 1993). They appear to provide superior levels of performance when compared with unconstrained conventional models. In many practical situations, however, we have - in addition to the spatial interaction data itself - some information about various accounting constraints on the predicted flows. In principle, there are two ways to incorporate accounting constraints in neural spatial interaction modeling. The required constraint properties can be built into the post-processing stage, or they can be built directly into the model structure. While the first way is relatively straightforward, it suffers from the disadvantage of being inefficient. It will also result in a model which does not inherently respect the constraints. Thus we follow the second way. In this paper we present a novel class of neural spatial interaction models that incorporate origin-specific constraints into the model structure using product units rather than summation units at the hidden layer and softmax output units at the output layer. Product unit neural networks are powerful because of their ability to handle higher order combinations of inputs. But parameter estimation by standard techniques such as the gradient descent technique may be difficult. The performance of this novel class of spatial interaction models will be demonstrated by using the Austrian interregional traffic data and the conventional singly constrained spatial interaction model of the gravity type as benchmark. References Fischer M M (1998) Computational neural networks: A new paradigm for spatial analysis Environment and Planning A 30 (10): 1873-1891 Fischer M M, Gopal S (1994) Artificial neural networks: A new approach to modelling interregional telecommunciation flows, Journal of Regional Science 34(4): 503-527 Openshaw S (1993) Modelling spatial interaction using a neural net. In Fischer MM, Nijkamp P (eds) Geographical information systems, spatial modelling, and policy evaluation, pp. 147-164. Springer, Berlin

Frauds in Telecommunication Traffic

Tato diplomová práce se zabývá problematikou podvodného chování (angl. frauds) v telefonním provozu a návrhy postupů na jejich detekci. Jako hlavní komponentou řešení byl použit open-source aplikační rámec Hadoop. Byly provedeny detekce různých typů fraudů na modifikovaných CDR záznamech. Na základě získaných grafických výstupů bylo vyhodnoceno, zda jsme schopni tyto fraudy v telefonním provozu detekovat. Pro získání grafických výstupů byly použity skripty psané v jazyce Python a grafický editor yEd. Ze získaných výsledků jsme byli schopni určit podezřelé aktivity s vlastnostmi charakteristickými pro námi zvolené typy fraudů, z čehož vyplývá, že naše návrhy řešení pro detekci fungují a simulace byly úspěšné.This master thesis deals with a topic of frauds in telephone traffic. It designs possible solutions for fraud detection. The main component of the solution is the open source framework Hadoop. Fraud detection were done on modified CDRs. Evaluation based on graphic outputs made the detection of frauds in the telephone traffic possible. The graphic outputs were obtained from the scripts written in Python and graphical editor yEd. Based on the graphical outputs we were able to identify suspicious activity with characteristics of the chosen type of frauds. This means our solution for frauds detection works and the simulations were successful