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Belo O.,University of Minho | Correia H.,Portugal Telecom Inovacao e Sistemas SA | Rodrigues P.,University of Minho | Barros R.,University of Minho
2016 6th International Conference on Innovative Computing Technology, INTECH 2016 | Year: 2016

Today dashboards are a clear factor of differentiation for decision-makers, providing critical business indicators in useful time. They are very important data visualization mechanisms, simple to interpret, easy to deal, and fast on showing pertinent data. Dashboards provide means for reducing time of information analysis, disposing business indicators in quite understandable and attractive interface platforms - a 'simple and beautiful' way to support business analysis. However, they use to be static software artifacts having not the ability to evolve, to adapt by themselves to new user needs, tendencies or preferences. In order to provide such abilities, we designed and implemented a personalization system for data visualization platforms. All system's services, ranging from data gathering to data profiling, were developed using a community of autonomous agents with the ability to act together using a private data cloud as a cooperative environment. In this paper we present how the system was conceived, its functional architecture and services, and how agents were implemented, especially the ones related to the personalization of business dashboards. © 2016 IEEE.

Santos D.,Telecommunications Institute of Portugal | Sargento S.,Telecommunications Institute of Portugal | Sargento S.,Portugal Telecom Inovacao e Sistemas SA
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | Year: 2015

Nowadays, we have witnessed an exponential growth of the traffic generated by users in mobile communications networks. This need for a greater capacity in mobile networks raises problems for operators, because the demand for network capacity is not always accompanied by the evolution of the available technologies. This represents problems in access networks that result in failures in the customer service and losses to the operator. It is quite important that the service is the best possible for both client and the operator: preventing and resolving network congestion is a common interest. The quality of service is also an important point of great concern, that requires to evaluate the service provided in order to achieve the best satisfaction from the user. However, many challenges still need to be surpassed on current mobile networks. This paper identifies and resolves cases of congestion in mobile networks, as well as it infers the quality of services provided to the customer. It proposes and implements an architecture that is able to identify problems in access networks, through network monitoring, using metrics gathered by a network management system that gives Key Performance Indicators (KPIs) evaluating the network, and through clients’ information for a specific cell, obtained through probing. Then, a Call Admission Control (CAC) module in the 3GPP Policy and Charging Rules Function (PCRF) is in charge of applying a rule set designed to resolve the case of the detected congestion. The policies chosen directly affect the users in the congested cell, causing the levels of occupancy to drop, and consequently, the cell resources to become stable. Several congestion use cases are identified and demonstrated, which show the effectiveness of the rules applied to the network, services and users. © 2015, Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, All rights Reserved.

Salvador A.,University of Aveiro | Nogueira J.,University of Aveiro | Nogueira J.,Portugal Telecom Inovacao e Sistemas SA | Sargento S.,University of Aveiro
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | Year: 2015

Quality of Experience (QoE) is a crucial characteristic of any multimedia service and must be accounted for during the service development and planning stages. Nonetheless, given its subjective nature, it is extremely difficult to use analytical methods to estimate the average Mean Opinion Score (MOS). Traditional progressive multimedia streaming is a well researched topic with respect to QoE, however, modern streaming services relying on advanced adaptive video streaming technologies, with specific characteristics, have yet to have an all-encompassing method for QoE estimation, as research work tend to focus on only one, or a small subset, of the technology’s aspects, such as the impact of buffering events, bit-rate change frequency, or initial playout delay. This paper proposes a model for determining the QoE estimate of a playback session of HTTP adaptive video streaming, encompassing its complete range of characteristics. Several key-metrics are extracted throughout the playback session, and then analyzed by an analytical method able to predict the consumers’ QoE. A subjective QoE survey is conducted according to industry’s best practices and recommendations in order to validate the proposed models. The obtained results show that both subjective and objective estimations produce similar results, hence validating the proposed model. © 2015, Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, All rights Reserved.

Pardal G.,University of Aveiro | Soares J.,University of Aveiro | Soares J.,Portugal Telecom Inovacao e Sistemas S.A | Gouveia R.,University of Aveiro | Sargento S.,University of Aveiro
Proceedings - IEEE Symposium on Computers and Communications | Year: 2016

Considering the growth of customers craving for complex services like IPTV, cloud storage, and online gaming, traditional networking is quickly becoming an obsolete technology. The new networking paradigm, Software Defined Networking (SDN), in combination with the recent communication protocol, OpenFlow, brings a new perspective to the operator and cloud provider's core networks by providing new autonomous tools. This paper proposes and evaluates a new SDN control mechanism that allows the definition of dedicated connectivity service within an operator network, making it possible to easily provide and support cloud services to the end user. It takes advantage of the combination of SDN and Cloud Computing, and further benefits the automation of both technologies, which empowers the operator to provide faster services to its users, such as virtual machine instantiation with automatic network creation. The evaluation of the proposed approach shows that the most time consuming phase is the installation of the OpenFlow rules in the network: in a network of 128 nodes, it takes around 250msec to both install and remove connections. © 2015 IEEE.

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