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Ljubljana, Slovenia

Svigelj A.,Jozef Stefan Institute | Sernec R.,Telekom Slovenije | Alic K.,Jozef Stefan Institute
IEEE Network | Year: 2015

Nowadays, networks have to be able to cope with ever increasing traffic demands in order to deliver the desired quality to end users. Thus, proper network planning is essential in order to preserve telecom revenues by reduced income per bandwidth unit. This article addresses a user-centric approach to network and user traffic modeling that has been validated and used in the process of introducing, optimizing, and planning new services at the Slovenian national telecom operator and service provider, Telekom Slovenije d.d. The proposed approach is based on the end users and their user group profiles that are founded on real measurements from the observed telecommunication network consisting of more than 1000 MSANs and more than 300,000 subscribers. The proposed approach has been successfully validated, showing that for the observed period the modeled link load deviates less than 5 percent from the measurements. Furthermore, in the presented case study the proposed approach is used successfully in the process of introducing the Fast Channel Change service. © 2015 IEEE.

Osterman A.,Telekom Slovenije
Elektrotehniski Vestnik/Electrotechnical Review | Year: 2012

Parallel computing is in expanding phase in GIS applications. A very attractive solution for parallel computing are the NVIDIA graphic cards, with a parallel computing platform and the CUDA (Compute Unified Device Architecture) programming model. The basis for this paper is the r:los module used to calculate optical visibility (LOS- Line of Sight), which is already implemented in the GRASS GIS environment. A completely new r:cuda:los module with the same functionality as the r:los module is presented. By using the r:cuda:los module for radio planning purposes of limiting the computation along the vertical and horizontal angle is also make possible. Visibility is calculated for each slice. The responsibility for the calculation of each slice is with its own thread from the parallel processor. At the size of the map of 28161 x 17921 points with the resolution 12; 5mx 12; 5m, the computation time is 18 s. In parallel computing the GIS data, the performance can be one, two or even three size classes faster than in the sequential computing.

Sedlar U.,University of Ljubljana | Volk M.,University of Ljubljana | Sterle J.,University of Ljubljana | Kos A.,University of Ljubljana | Sernec R.,Telekom Slovenije
IEEE Network | Year: 2012

This article describes the architecture and design of an IPTV network monitoring system and some of the use cases it enables. The system is based on distributed agents within IPTV terminal equipment (set-top box), which collect and send the data to a server where it is analyzed and visualized. In the article we explore how large amounts of collected data can be utilized for monitoring the quality of service and user experience in real time, as well as for discovering trends and anomalies over longer periods of time. Furthermore, the data can be enriched using external data sources, providing a deeper understanding of the system by discovering correlations with events outside of the monitored domain. Four supported use cases are described, among them using weather information for explaining away the IPTV quality degradation. The system has been successfully deployed and is in operation at the Slovenian IPTV provider Telekom Slovenije. © 1986-2012 IEEE.

Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2013.6.1 | Award Amount: 4.75M | Year: 2014

SUNSEED proposes an evolutionary approach to utilisation of already present communication networks from both energy and telecom operators. These can be suitably connected to form a converged communication infrastructure for future smart energy grids offering open services. Life cycle of such communication network solutions consists of six steps: overlap, interconnect, interoperate, manage, plan and open. Joint communication networking operations steps start with analysis of regional overlap of energy and telecommunications operator infrastructures. Geographical overlap of energy and communications infrastructures identifies vital DSO energy and support grid locations (e.g. distributed energy generators, transformer substations, cabling, ducts) that are covered by both energy and telecom communication networks. Coverage can be realised with known wireline (e.g. copper, fiber)or wireless and mobile (e.g. WiFi, 4G) technologies. Interconnection assures end-2-end secure communication on the physical layer between energy and telecom, whereas interoperation provides network visibility and reach of smart grid nodes from both operator (utility) sides. Monitoring, control and management gathers measurement data from wide area of sensors and smart meters and assures stable distributed energy grid operation by using novel intelligent real time analytical knowledge discovery methods. For full utilisation of future network planning, we will integrate various public databases. Applications build on open standards (W3C) with exposed application programming interfaces (API) to 3rd parties enable creation of new businesses related to energy and communication sectors (e.g. virtual power plant operators, energy services providers for optimizing home energy use) or enable public wireless access points (e.g. WiFi nodes at distributed energy generator locations). SUNSEED life cycle steps promise much lower investments and total cost of ownership for future smart energy grids with dense distributed energy generation and prosumer involvement.

Droftina U.,Telekom Slovenije | Stular M.,Telekom Slovenije | Kosir A.,University of Ljubljana
Advances in Data Analysis and Classification | Year: 2015

Churn prediction has received much attention in the last decade. With the evolution of social networks and social network analysis tools in recent years, the consideration of social ties in churn prediction has proven promising. One possibility is to use energy diffusion models to model the spread of influence through a social network. This paper proposes a novel churn prediction diffusion model based on sociometric clique and social status theory. It describes the concept of energy in the diffusion model as an opinion of users, which is transformed to user influence using the derived social status function. Furthermore, a novel diffusion model prediction scheme applicable to a single user or a small subset of users is described: the Targeted User Subset Churn Prediction Scheme. The scheme allows fast churn prediction using limited computing resources. The diffusion model is evaluated on a real dataset of users obtained from the largest Slovenian mobile service provider, using the F-measure and lift curve. The empirical results show a significant improvement in prediction accuracy of the proposed method compared with the basic spreading activation technique (SPA) diffusion model. More specifically, our approach outperforms a basic SPA diffusion model by 116 % in terms of lift in the fifth percentile. © 2014, The Author(s).

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