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    Integration of Legacy Appliances into Home Energy Management Systems

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    The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS

    NILM techniques for intelligent home energy management and ambient assisted living: a review

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    The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.Agência financiadora: Programa Operacional Portugal 2020 and Programa Operacional Regional do Algarve 01/SAICT/2018/39578 Fundação para a Ciência e Tecnologia through IDMEC, under LAETA: SFRH/BSAB/142998/2018 SFRH/BSAB/142997/2018 UID/EMS/50022/2019 Junta de Comunidades de Castilla-La-Mancha, Spain: SBPLY/17/180501/000392 Spanish Ministry of Economy, Industry and Competitiveness (SOC-PLC project): TEC2015-64835-C3-2-R MINECO/FEDERinfo:eu-repo/semantics/publishedVersio

    Inefficiencies in Digital Advertising Markets

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    Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

    VoIP Quality Assessment Technologies

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    Avaliação da qualidade de experiência de vídeo em várias tecnologias

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    Mestrado em Engenharia Eletrónica e TelecomunicaçõesNowadays the internet is associated with many services. Combined with this fact, there is a marked increase of the users joining this service. In this perspective, it is required that the service providers guarantee a minimum quality to the network services. The Quality of Experience of services is quite crucial in the development of services in networks. Also noteworthy, the tra c increase in multimedia services, including video streaming, increases the probability of congesting the networks. In the perspective of the service provider, the monitoring is a solution to avoid saturation in network. This way, this dissertation proposes to develop a platform that allows a multimedia tra c monitoring in the Meo Go service provided by the operator Portugal Telecom Communications. The architecture of the adaptive streaming over HTTP has been studied and tested to obtain the quality of experience metrics. This adaptive streaming technique presents the smooth streaming, an architecture made by Microsoft company, and it is used in the Meo Go service. Then, it is monitored the metrics obtained with the video player. This analysis is done objectively and subjectively. In this phase, the objective implementation of the method allows to obtain the prediction value of the Quality of Experience by consumers. The selected metrics were derived from the state / performance of network and terminal device. The obtained metrics aim to simulate human action in video score quality. Otherwise, subjectively, it is conducted a survey based in a questionnaire to compare methods. In this phase it was created an on-line platform to allow the obtain a greater number of rankings and data processing. In the obtained results, rstly in the smooth streaming player, it is shown the adaptive streaming implementation technique. On the next phase, test scenarios were created to demonstrate the functioning of the method in many cases, with greater relevance for those ones with higher dynamic complexity. From the perspective of subjective and objective methods, these have values that con rm the architecture of the implemented module. Over time, the performance of the scoring the quality of video streaming services approaches the one in a human mental action.Nos dias de hoje a Internet é um dos meios com mais serviços associados. Conjugado a este facto, existe um acentuado aumento de utilizadores a aderir a este serviço. Nesta perspectiva existe a necessidade de garantir uma qualidade mínima por parte dos prestadores de serviços. A Qualidade de Experiência que os consumidores têm dos serviços é bastante crucial no desenvolvimento e optimização dos serviços nas redes. É ainda de salientar que o aumento do tráfego multimédia, nomeadamente os streamings de vídeo, apresenta incrementos na probabilidade de as redes se congestionarem. Na perspectiva do prestador de serviços a monitorização é a solução para evitar a saturação total. Neste sentido, esta dissertação pretende desenvolver uma plataforma que permite a monitorização do tráfego de multimédia do serviço do Meo Go, fornecido pela operadora Portugal Telecom Comunicações. Neste trabalho foi necessário investigar e testar a arquitectura do streaming adaptativo sobre HTTP para ser possível obter métricas de qualidade de experiência. Este streaming adaptativo apresenta a técnica de smooth streaming, sendo esta arquitectura projectada pela empresa Microsoft e utilizada no serviço Meo Go. Posteriormente foram monitorizadas as métricas que se obtiveram no player de vídeo. Esta análise foi realizada de forma objectiva e subjectiva. Nesta fase da implementação objectiva do método em que se pretende obter uma predição do valor de Qualidade de Experiência por parte do consumidor, foram seleccionadas as métricas oriundas do estado/desempenho da rede e do dispositivo terminal. As métricas obtidas entram num processo de tratamento que pretende simular a ação humana nas classificações da qualidade dos vídeos. De outra forma, subjectivamente, foi realizada uma pesquisa, com base num questionário, de modo a comparar os métodos. Nesta etapa foi gerada uma plataforma online que possibilitou obter um maior número de classificações dos vídeos para posteriormente se proceder ao tratamento de dados. Nos resultados obtidos, primeiramente ao nível do player de smooth streaming, estes permitem analisar a técnica de implementação de streaming adaptativo. Numa fase seguinte foram criados cenários de teste para comprovar o funcionamento do método em diversas situações, tendo com maior relevância aqueles que contêm dinâmicas mais complexas. Na perspectiva dos métodos subjectivo e objectivo, estes apresentam valores que confirmam a arquitectura do módulo implementado. Adicionalmente, o desempenho do método em classificar a qualidade de serviço de vídeo streaming, ao longo do tempo, apresentou valores que se aproximam da dinâmica esperada numa ação mental humana

    Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

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    Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

    Network and service monitoring in heterogeneous home networks

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    Home networks are becoming dynamic and technologically heterogeneous. They consist of an increasing number of devices which offer several functionalities and can be used for many different services. In the home, these devices are interconnected using a mixture of networking technologies (for example, Ethernet, Wifi, coaxial cable, or power-line). However, interconnecting these devices is often not easy. The increasing heterogeneity has led to significant device- and service-management complexity. In addition, home networks provide a critical "last meters" access to the public telecom and Internet infrastructure and have a dramatic impact on to the end-to-end reliability and performance of services from these networks. This challenges service providers not only to maintain a satisfactory quality of service level in such heterogeneous home networks, but also to remotely monitor and troubleshoot them. The present thesis work contributes research and several solutions in the field of network and service monitoring in home networks, mainly in three areas: (1) providing automatic device- and service-discovery and configuration, (2) remote management, and (3) providing quality of service (QoS). With regard to the first area, current service discovery technology is designed to relieve the increasing human role in network and service administration. However, the relevant Service Discovery Protocols (SDPs) are lacking crucial features namely: (1) they are not platform- and network-independent, and (2) they do not provide sufficient mechanisms for (device) resource reservation. Consequently, devices implementing different SDPs cannot communicate with each other and share their functionalities and resources in a managed way, especially when they use different network technologies. As a solution to the first problem, we propose a new proxy server architecture that enables IP-based devices and services to be discovered on non-IP based network and vice versa. We implemented the proxy architecture using UPnP respectively Bluetooth SDP as IP- and non-IP-based SDPs. The proxy allows Bluetooth devices and UPnP control points to discover, access, and utilize services located on the other network. Validation experiments with the proxy prototype showed that seamless inter-working can be achieved keeping all proxy functionalities on a single device, thus not requiring modification of currently existing UPnP and Bluetooth end devices. Although the proxy itself taxes the end-to-end performance of the service, it is shown to be still acceptable for an end user. For mitigating resource conflicts in SDPs, we propose a generic resource reservation scheme with properties derived from common SDP operation. Performance studies with a prototype showed that this reservation scheme significantly improves the scalability and sustainability of service access in SDPs, at a minor computational cost. With regard to the second area, it is known that the end-to-end quality of Internet services depends crucially on the performance of the home network. Consequently, service providers require the ability to monitor and configure devices in the home network, behind the home gateway (HG). However, they can only put limited requirements to these off-the-shelf devices, as the consumer electronics market is largely outside their span of control. Therefore they have to make intelligent use of the given device control and management protocols. In this work, we propose an architecture for remote discovery and management of devices in a highly heterogeneous home network. A proof-of-concept is developed for the remote management of UPnP devices in the home with a TR-069/UPnP proxy on the HG. Although this architecture is protocol specific, it can be easily adapted to other web-services based protocols. Service providers are also asking for diagnostic tools with which they can remotely troubleshoot the home networks. One of these tools should be able to gather information about the topology of the home network. Although topology discovery protocols already exist, nothing is known yet about their performance. In this work we propose a set of key performance indicators for home network topology discovery architectures, and how they should be measured. We applied them to the Link-Layer Topology Discovery (LLTD) protocol and the Link-Layer Discovery Protocol (LLDP). Our performance measurement results show that these protocols do not fulfill all the requirements as formulated by the service providers. With regard to the third area, current QoS solutions are mostly based on traffic classification. Because they need to be supported by all devices in the network, they are relatively expensive for home networks. Furthermore, they are not interoperable between different networking technologies. Alternative QoS provision techniques have been proposed in the literature. These techniques require end-user services to pragmatically adapt their properties to the actual condition of the network. For this, the condition of the home network in terms of its available bandwidth, delay, jitter, etc., needs to be known in real time. Appropriate tools for determining the available home network resources do not yet exist. In this work we propose a new method to probe the path capacity and available bandwidth between a server and a client in a home network. The main features of this method are: (a) it does not require adaptation of existing end devices, (b) it does not require pre-knowledge of the link-layer network topology, and (c) it is accurate enough to make reliable QoS predictions for the most relevant home applications. To use these predictions for effective service- or content-adaptation or admission control, one should also know how the state of the home network is expected to change immediately after the current state has been probed. However, not much is known about the stochastic properties of traffic in home networks. Based on a relatively small set of traffic observations in several home networks in the Netherlands, we were able to build a preliminary model for home network traffic dynamics
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